├── content ├── tags │ ├── image │ │ └── contents.lr │ ├── survey │ │ └── contents.lr │ ├── genetic │ │ └── contents.lr │ ├── spanish │ │ └── contents.lr │ ├── regression │ │ └── contents.lr │ ├── contents.lr │ └── classification │ │ └── contents.lr ├── contents.lr ├── sitemap.xml │ └── contents.lr ├── german-credit │ └── contents.lr ├── vote │ ├── contents.lr │ └── vote.csv ├── glass │ ├── contents.lr │ ├── glass.csv │ └── glass.arff ├── all-aml-leukemia │ └── contents.lr ├── travel-survey │ └── contents.lr ├── about │ └── contents.lr ├── labor │ ├── contents.lr │ ├── labor.csv │ └── labor.arff ├── breast-cancer │ ├── contents.lr │ ├── breast-cancer.csv │ └── breast-cancer.arff ├── diabetes │ └── contents.lr ├── letter │ └── contents.lr ├── tic-tac-toe │ └── contents.lr ├── ionosphere │ └── contents.lr ├── car │ └── contents.lr ├── iris │ ├── contents.lr │ ├── iris.csv │ └── iris.arff ├── zoo │ ├── contents.lr │ ├── zoo.csv │ └── zoo.arff ├── soybean │ └── contents.lr └── divorce │ ├── contents.lr │ └── divorce.csv ├── biglittledata.lektorproject ├── models ├── tags.ini ├── page.ini ├── datasets.ini ├── tag.ini └── dataset.ini ├── ipfs ├── ipfs.service ├── add-ipfs.yml └── install-ipfs.yml ├── templates ├── page.html ├── sitemap.xml ├── tag.html ├── index.html ├── macros │ └── pagination.html ├── layout.html └── dataset.html ├── README.md └── assets └── static └── style.css /content/tags/image/contents.lr: -------------------------------------------------------------------------------- 1 | name: image 2 | -------------------------------------------------------------------------------- /content/tags/survey/contents.lr: -------------------------------------------------------------------------------- 1 | name: survey 2 | -------------------------------------------------------------------------------- /content/tags/genetic/contents.lr: -------------------------------------------------------------------------------- 1 | name: genetic 2 | -------------------------------------------------------------------------------- /content/tags/spanish/contents.lr: -------------------------------------------------------------------------------- 1 | name: spanish 2 | -------------------------------------------------------------------------------- /content/tags/regression/contents.lr: -------------------------------------------------------------------------------- 1 | name: regression 2 | -------------------------------------------------------------------------------- /content/contents.lr: -------------------------------------------------------------------------------- 1 | _model: datasets 2 | --- 3 | _template: index.html 4 | -------------------------------------------------------------------------------- /content/sitemap.xml/contents.lr: -------------------------------------------------------------------------------- 1 | _template: sitemap.xml 2 | --- 3 | _model: none 4 | -------------------------------------------------------------------------------- /content/tags/contents.lr: -------------------------------------------------------------------------------- 1 | _model: tags 2 | --- 3 | _slug: tags 4 | --- 5 | _template: index.html 6 | -------------------------------------------------------------------------------- /content/tags/classification/contents.lr: -------------------------------------------------------------------------------- 1 | name: classification 2 | --- 3 | _model: tag 4 | --- 5 | _template: tag.html 6 | -------------------------------------------------------------------------------- /biglittledata.lektorproject: -------------------------------------------------------------------------------- 1 | [project] 2 | name = biglittledata 3 | locale = en_US 4 | url = "https://www.biglittledata.net" 5 | url_style = "relative" 6 | -------------------------------------------------------------------------------- /models/tags.ini: -------------------------------------------------------------------------------- 1 | [model] 2 | name = Tags 3 | label = Tags 4 | hidden = yes 5 | protected = yes 6 | 7 | [children] 8 | model = tag 9 | order_by = name 10 | 11 | -------------------------------------------------------------------------------- /models/page.ini: -------------------------------------------------------------------------------- 1 | [model] 2 | name = Page 3 | label = {{ this.title }} 4 | 5 | [fields.title] 6 | label = Title 7 | type = string 8 | 9 | [fields.body] 10 | label = Body 11 | type = markdown 12 | -------------------------------------------------------------------------------- /ipfs/ipfs.service: -------------------------------------------------------------------------------- 1 | [Unit] 2 | Description=IPFS daemon 3 | After=network.target 4 | 5 | [Service] 6 | ExecStart=/usr/local/bin/ipfs daemon 7 | Restart=on-failure 8 | 9 | [Install] 10 | WantedBy=default.target 11 | -------------------------------------------------------------------------------- /templates/page.html: -------------------------------------------------------------------------------- 1 | {% extends "layout.html" %} 2 | {% block title %}{{ this.title }}{% endblock %} 3 | {% block body %} 4 |

{{ this.title }}

5 |
6 | {{ this.body }} 7 |
8 | {% endblock %} 9 | -------------------------------------------------------------------------------- /content/german-credit/contents.lr: -------------------------------------------------------------------------------- 1 | name: German Credit 2 | --- 3 | attributes: 21 4 | --- 5 | description: German Credit data 6 | --- 7 | instances: 1000 8 | --- 9 | license: Public Domain 10 | --- 11 | tags: classification 12 | -------------------------------------------------------------------------------- /models/datasets.ini: -------------------------------------------------------------------------------- 1 | [model] 2 | name = Datasets 3 | label = Datasets 4 | hidden = yes 5 | protected = yes 6 | 7 | [children] 8 | model = dataset 9 | order_by = name 10 | 11 | [pagination] 12 | enabled = no 13 | per_page = 10 14 | -------------------------------------------------------------------------------- /models/tag.ini: -------------------------------------------------------------------------------- 1 | [model] 2 | name = Tag 3 | label = {{ this.name }} 4 | hidden = yes 5 | 6 | [children] 7 | replaced_with = site.query('/').filter(F.tags.contains(this.name)) 8 | 9 | [fields.name] 10 | label = Name 11 | type = string 12 | -------------------------------------------------------------------------------- /content/vote/contents.lr: -------------------------------------------------------------------------------- 1 | name: Vote 2 | --- 3 | attributes: 16 4 | --- 5 | description: 1984 United Stated Congressional Voting Records; Classify as Republican or Democrat 6 | --- 7 | instances: 435 8 | --- 9 | license: Public Domain 10 | --- 11 | tags: classification 12 | -------------------------------------------------------------------------------- /content/glass/contents.lr: -------------------------------------------------------------------------------- 1 | name: Glass 2 | --- 3 | attributes: 10 4 | --- 5 | description: From USA Forensic Science Service; 6 types of glass; defined in terms of their oxide content (i.e. Na, Fe, K, etc). 6 | --- 7 | instances: 214 8 | --- 9 | license: Public Domain 10 | --- 11 | tags: classification 12 | -------------------------------------------------------------------------------- /templates/sitemap.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | {%- for page in [site.root] if page != this recursive %} 4 | {{ page|url(external=true) }} 5 | {{- loop(page.children) }} 6 | {%- endfor %} 7 | 8 | -------------------------------------------------------------------------------- /templates/tag.html: -------------------------------------------------------------------------------- 1 | {% extends "layout.html" %} 2 | {% block title %}Datasets tagged {{ this.name }}{% endblock %} 3 | {% block body %} 4 |

Tag: {{ this.name }}

5 |

Datasets:

6 | 13 | {% endblock %} 14 | -------------------------------------------------------------------------------- /content/all-aml-leukemia/contents.lr: -------------------------------------------------------------------------------- 1 | name: ALL-AML Leukemia 2 | --- 3 | attributes: 7130 4 | --- 5 | description: This dataset contains genetic expression arrays, enabling us to predict which kind of Leukemia has a person based on its genetic activity (ALL or AML) and also which genes are more important. 6 | --- 7 | instances: 72 8 | --- 9 | license: Public Domain 10 | --- 11 | tags: classification, genetic 12 | -------------------------------------------------------------------------------- /ipfs/add-ipfs.yml: -------------------------------------------------------------------------------- 1 | - hosts: all 2 | become_method: sudo 3 | remote_user: pi 4 | name: Add files to IPFS 5 | vars_prompt: 6 | - name: ipfs 7 | prompt: Put here the IPFS hash to pin 8 | private: no 9 | tasks: 10 | - name: Download files 11 | command: "ipfs get /ipfs/{{ ipfs }}" 12 | become: yes 13 | - name: Pin files 14 | command: "ipfs pin add /ipfs/{{ ipfs }}" 15 | become: yes 16 | 17 | -------------------------------------------------------------------------------- /content/travel-survey/contents.lr: -------------------------------------------------------------------------------- 1 | name: Travel Survey 2 | --- 3 | attributes: 12 4 | --- 5 | description: 6 | 7 | Travel Survey contains the result of a survey about travel made at Valladolid University. The questions, in Spanish, are all about the habits of travelers on their last travel. 8 | 9 | This dataset was made by [Adrián Arroyo](http://adrianistan.eu), Pablo Valdunciel, Duero Cuadrilleo and Héctor Sáenz. 10 | --- 11 | instances: 217 12 | --- 13 | license: Public Domain 14 | --- 15 | tags: spanish, survey 16 | -------------------------------------------------------------------------------- /content/about/contents.lr: -------------------------------------------------------------------------------- 1 | _model: page 2 | --- 3 | title: About BigLittleData 4 | --- 5 | body: 6 | 7 | This website is a repository of datasets under open licenses, running under [IPFS](https://ipfs.io/). The main objectives are: 8 | 9 | * Easy interface to download datasets in different formats 10 | * Simple webpage to be able to be used anywhere 11 | * Distributed content using IPFS underlaying. 12 | 13 | To add or request datasets, go to: [https://github.com/aarroyoc/biglittledata](https://github.com/aarroyoc/biglittledata) 14 | -------------------------------------------------------------------------------- /templates/index.html: -------------------------------------------------------------------------------- 1 | {% extends "layout.html" %} 2 | {% block title %}BigLittleData{% endblock %} 3 | {% block body %} 4 |

Welcome to BigLittleData!

5 |
6 | A curated dataset repository with open licenses for machine learning, big data and statistics. 7 |

Datasets

8 | 15 |
16 | {% endblock %} 17 | -------------------------------------------------------------------------------- /models/dataset.ini: -------------------------------------------------------------------------------- 1 | [model] 2 | name = Dataset 3 | label = {{ this.name }} 4 | 5 | [fields.name] 6 | label = Name 7 | type = string 8 | 9 | [fields.description] 10 | label = Description 11 | type = markdown 12 | 13 | [fields.attributes] 14 | label = Atributtes 15 | type = integer 16 | 17 | [fields.instances] 18 | label = Instances 19 | type = integer 20 | 21 | [fields.license] 22 | label = License 23 | type = string 24 | 25 | [fields.tags] 26 | label = Tags 27 | type = checkboxes 28 | source = site.query('/tags') 29 | 30 | [attachments] 31 | enabled = yes 32 | -------------------------------------------------------------------------------- /templates/macros/pagination.html: -------------------------------------------------------------------------------- 1 | {% macro render_pagination(pagination) %} 2 | 15 | {% endmacro %} 16 | -------------------------------------------------------------------------------- /content/labor/contents.lr: -------------------------------------------------------------------------------- 1 | name: Labor 2 | --- 3 | attributes: 16 4 | --- 5 | description: 6 | 7 | Final settlements in labor negotitions in Canadian industry. 8 | 9 | Testing concept learning software, in particular an experimental method to learn two-tiered concept descriptions. The data was used to learn the description of an acceptable and unacceptable contract. The unacceptable contracts were either obtained by interviewing experts, or by inventing near misses. 10 | --- 11 | instances: 57 12 | --- 13 | license: Public Domain 14 | --- 15 | tags: classification 16 | -------------------------------------------------------------------------------- /content/breast-cancer/contents.lr: -------------------------------------------------------------------------------- 1 | name: Breast Cancer 2 | --- 3 | attributes: 9 4 | --- 5 | description: 6 | 7 | Breast Cancer Data. This is one of three domains provided by the Oncology Institute that has repeatedly appeared in the machine learning literature. (See also lymphography and primary-tumor.) 8 | 9 | This data set includes 201 instances of one class and 85 instances of another class. The instances are described by 9 attributes, some of which are linear and some are nominal. 10 | --- 11 | instances: 286 12 | --- 13 | license: Public Domain 14 | --- 15 | tags: classification 16 | -------------------------------------------------------------------------------- /content/diabetes/contents.lr: -------------------------------------------------------------------------------- 1 | name: Diabetes 2 | --- 3 | attributes: 9 4 | --- 5 | description: This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage. 6 | --- 7 | instances: 768 8 | --- 9 | tags: classification 10 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # BigLittleData 2 | 3 | A curated dataset repository with open licenses for machine learning, big data and statistics. It runs under [IPFS](https://ipfs.io/) using Lektor to build the website. The main objectives are: 4 | 5 | * Easy interface to download datasets in different formats 6 | * Simple webpage to be able to be used anywhere 7 | * Distributed content using IPFS underlaying. 8 | 9 | ## Building 10 | 11 | Install [Lektor](https://www.getlektor.com/) 12 | 13 | ``` 14 | git clone git@github.com:aarroyoc/biglittledata.git 15 | lektor server (to add/edit/delete datasets) 16 | lektor build -O build 17 | cd build 18 | ipfs add -r . 19 | (get last hash and modify dnslink TXT in DNS provider, pin and keep ipfs alive) 20 | ``` 21 | HTTPS support thanks to CloudFlare IPFS gateway 22 | -------------------------------------------------------------------------------- /content/letter/contents.lr: -------------------------------------------------------------------------------- 1 | name: Letter Image Recognition 2 | --- 3 | attributes: 16 4 | --- 5 | description: 6 | 7 | The objective is to identify each of a large number of black-and-white rectangular pixel displays as one of the 26 capital letters in the English alphabet. The character images were based on 20 different fonts and each letter within these 20 fonts was randomly distorted to produce a file of 20,000 unique stimuli. Each stimulus was converted into 16 primitive numerical attributes (statistical moments and edge counts) which were then scaled to fit into a range of integer values from 0 through 15. We typically train on the first 16000 items and then use the resulting model to predict the letter category for the remaining 4000. 8 | --- 9 | instances: 20000 10 | --- 11 | license: Public Domain 12 | --- 13 | tags: classification, image 14 | -------------------------------------------------------------------------------- /assets/static/style.css: -------------------------------------------------------------------------------- 1 | body { 2 | font-family: 'Verdana', sans-serif; 3 | margin: 50px 25px; 4 | } 5 | 6 | a { 7 | color: #2a99b6; 8 | } 9 | 10 | a:hover { 11 | color: #33bbdf; 12 | } 13 | 14 | header, footer, div.page { 15 | max-width: 760px; 16 | width: calc(90vw - 60px); 17 | margin: 0 auto; 18 | background: #daeef3; 19 | padding: 20px 30px; 20 | } 21 | 22 | header h1 { 23 | color: #169bbd; 24 | margin: 0; 25 | font-weight: normal; 26 | font-size: 42px; 27 | } 28 | 29 | header nav ul { 30 | list-style: none; 31 | margin: 0; 32 | padding: 0; 33 | } 34 | 35 | header nav ul li { 36 | display: inline; 37 | margin: 0 8px 0 0; 38 | padding: 0; 39 | } 40 | 41 | div.page { 42 | background: #f1fbfe; 43 | } 44 | 45 | div.databox { 46 | display: flex; 47 | flex-direction: row; 48 | } 49 | div.databox > span { 50 | flex: 1; 51 | } 52 | -------------------------------------------------------------------------------- /content/tic-tac-toe/contents.lr: -------------------------------------------------------------------------------- 1 | name: Tic Tac Toe 2 | --- 3 | attributes: 9 4 | --- 5 | description: 6 | 7 | Tic-Tac-Toe Endgame database. 8 | 9 | This database encodes the complete set of possible board configurations at the end of tic-tac-toe games, where "x" is assumed to have played first. The target concept is "win for x" (i.e., true when "x" has one of 8 possible ways to create a "three-in-a-row"). 10 | 11 | ### Attributes 12 | (x=player x has taken, o=player o has taken, b=blank) 13 | 14 | 1. top-left-square: {x,o,b} 15 | 2. top-middle-square: {x,o,b} 16 | 3. top-right-square: {x,o,b} 17 | 4. middle-left-square: {x,o,b} 18 | 5. middle-middle-square: {x,o,b} 19 | 6. middle-right-square: {x,o,b} 20 | 7. bottom-left-square: {x,o,b} 21 | 8. bottom-middle-square: {x,o,b} 22 | 9. bottom-right-square: {x,o,b} 23 | 10. Class: {positive,negative} 24 | 25 | --- 26 | instances: 958 27 | --- 28 | license: Public Domain 29 | --- 30 | tags: classification 31 | -------------------------------------------------------------------------------- /content/ionosphere/contents.lr: -------------------------------------------------------------------------------- 1 | name: Ionosphere 2 | --- 3 | attributes: 35 4 | --- 5 | description: 6 | 7 | Classification of radar returns from the ionosphere. 8 | 9 | This radar data was collected by a system in Goose Bay, Labrador. This system consists of a phased array of 16 high-frequency antennas with a total transmitted power on the order of 6.4 kilowatts. See the paper for more details. The targets were free electrons in the ionosphere. "Good" radar returns are those showing evidence of some type of structure in the ionosphere. "Bad" returns are those that do not; their signals pass through the ionosphere. 10 | 11 | Received signals were processed using an autocorrelation function whose arguments are the time of a pulse and the pulse number. There were 17 pulse numbers for the Goose Bay system. Instances in this databse are described by 2 attributes per pulse number, corresponding to the complex values returned by the function resulting from the complex electromagnetic signal. 12 | --- 13 | instances: 351 14 | --- 15 | license: Public Domain 16 | --- 17 | tags: classification 18 | -------------------------------------------------------------------------------- /ipfs/install-ipfs.yml: -------------------------------------------------------------------------------- 1 | - hosts: all 2 | remote_user: pi 3 | become_method: sudo 4 | name: "Install IPFS" 5 | tasks: 6 | - name: Download IPFS 7 | get_url: 8 | url: "https://dist.ipfs.io/go-ipfs/v0.4.22/go-ipfs_v0.4.22_linux-arm.tar.gz" 9 | dest: /home/pi/ipfs.tar.gz 10 | - name: Extract IPFS 11 | unarchive: 12 | src: /home/pi/ipfs.tar.gz 13 | dest: /home/pi 14 | remote_src: yes 15 | - name: Copy IPFS 16 | command: cp /home/pi/go-ipfs/ipfs /usr/local/bin/ipfs 17 | become: yes 18 | - name: Check status 19 | stat: 20 | path: /root/.ipfs 21 | register: ipfs_folder 22 | become: yes 23 | - name: Init IPFS 24 | command: ipfs init 25 | become: yes 26 | when: not ipfs_folder.stat.exists 27 | - name: Copy IPFS systemd 28 | copy: 29 | src: ipfs.service 30 | dest: /etc/systemd/system/ipfs.service 31 | become: yes 32 | - name: Start IPFS daemon 33 | systemd: 34 | daemon_reload: yes 35 | enabled: yes 36 | name: ipfs 37 | state: restarted 38 | become: yes 39 | -------------------------------------------------------------------------------- /content/car/contents.lr: -------------------------------------------------------------------------------- 1 | name: Car 2 | --- 3 | attributes: 7 4 | --- 5 | description: 6 | 7 | Car Evaluation Database was derived from a simple hierarchical decision model originally developed for the demonstration of DEX, M. Bohanec, V. Rajkovic: Expert system for decision making. Sistemica 1(1), pp. 145-157, 1990.). The model evaluates cars according to the following concept structure: 8 | 9 | * CAR car acceptability 10 | * PRICE overall price 11 | * buying buying price 12 | * maint price of the maintenance 13 | * TECH technical characteristics 14 | * COMFORT comfort 15 | * doors number of doors 16 | * persons capacity in terms of persons to carry 17 | * lug_boot the size of luggage boot 18 | *safety estimated safety of the car 19 | 20 | ### Attributes 21 | 22 | buying: vhigh, high, med, low. 23 | maint: vhigh, high, med, low. 24 | doors: 2, 3, 4, 5more. 25 | persons: 2, 4, more. 26 | lug_boot: small, med, big. 27 | safety: low, med, high. 28 | class: unacc, acc, good, vgood 29 | --- 30 | instances: 1728 31 | --- 32 | license: Public Domain 33 | --- 34 | tags: classification 35 | -------------------------------------------------------------------------------- /content/iris/contents.lr: -------------------------------------------------------------------------------- 1 | _model: dataset 2 | --- 3 | name: Iris 4 | --- 5 | description: 6 | 7 | The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis. It is sometimes called Anderson's Iris data set because Edgar Anderson collected the data to quantify the morphologic variation of Iris flowers of three related species. Two of the three species were collected in the Gaspé Peninsula "all from the same pasture, and picked on the same day and measured at the same time by the same person with the same apparatus". 8 | 9 | The data set consists of 50 samples from each of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). Four features were measured from each sample: the length and the width of the sepals and petals, in centimeters. Based on the combination of these four features, Fisher developed a linear discriminant model to distinguish the species from each other. 10 | --- 11 | license: Public Domain 12 | --- 13 | task: classification 14 | --- 15 | upload_date: 2019-11-03 16 | --- 17 | tags: classification 18 | -------------------------------------------------------------------------------- /templates/layout.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | {% block title %}Welcome{% endblock %} — biglittledata 6 | 7 | 8 | 15 | 16 |
17 |

BigLittleData

18 | 28 |
29 |
30 | {% block body %}{% endblock %} 31 |
32 | 35 | 36 | -------------------------------------------------------------------------------- /content/zoo/contents.lr: -------------------------------------------------------------------------------- 1 | name: Zoo 2 | --- 3 | attributes: 18 4 | --- 5 | description: 6 | 7 | A simple database containing 17 Boolean-valued attributes. The "type" attribute appears to be the class attribute. Here is a breakdown of which animals are in which type: 8 | 9 | ### Class 10 | 11 | 1 -- (41) aardvark, antelope, bear, boar, buffalo, calf, cavy, cheetah, deer, dolphin, elephant, fruitbat, giraffe, girl, goat, gorilla, hamster, hare, leopard, lion, lynx, mink, mole, mongoose, opossum, oryx, platypus, polecat, pony, porpoise, puma, pussycat, raccoon, reindeer, seal, sealion, squirrel, vampire, vole, wallaby,wolf 12 | 13 | 2 -- (20) chicken, crow, dove, duck, flamingo, gull, hawk, kiwi, lark, ostrich, parakeet, penguin, pheasant, rhea, skimmer, skua, sparrow, swan, vulture, wren 14 | 15 | 3 -- (5) pitviper, seasnake, slowworm, tortoise, tuatara 16 | 17 | 4 -- (13) bass, carp, catfish, chub, dogfish, haddock, herring, pike, piranha, seahorse, sole, stingray, tuna 18 | 19 | 5 -- (4) frog, frog, newt, toad 20 | 21 | 6 -- (8) flea, gnat, honeybee, housefly, ladybird, moth, termite, wasp 22 | 23 | 7 -- (10) clam, crab, crayfish, lobster, octopus, scorpion, seawasp, slug, starfish, worm 24 | 25 | ### Attributes 26 | 27 | 1. animal name: Unique for each instance 28 | 2. hair: Boolean 29 | 3. feathers: Boolean 30 | 4. eggs: Boolean 31 | 5. milk: Boolean 32 | 6. airborne: Boolean 33 | 7. aquatic: Boolean 34 | 8. predator: Boolean 35 | 9. toothed: Boolean 36 | 10. backbone: Boolean 37 | 11. breathes: Boolean 38 | 12. venomous: Boolean 39 | 13. fins: Boolean 40 | 14. legs: Numeric (set of values: {0,2,4,5,6,8}) 41 | 15. tail: Boolean 42 | 16. domestic: Boolean 43 | 17. catsize: Boolean 44 | 18. type: Numeric (integer values in range [1,7]) 45 | --- 46 | instances: 101 47 | --- 48 | license: Public Domain 49 | --- 50 | tags: classification 51 | -------------------------------------------------------------------------------- /templates/dataset.html: -------------------------------------------------------------------------------- 1 | {% extends "layout.html" %} 2 | {% block title %}{{ this.name }}{% endblock %} 3 | {% block body %} 4 |

{{ this.name }}

5 |
Instances: {{ this.instances }}Attributes: {{ this.attributes }}
6 |
7 |
8 | {{ this.description }} 9 |
10 |

Downloads

11 | 16 | License: {{ this.license }} 17 | {% if this.tags %} 18 |

Tags: 19 | {% for t in this.tags -%} 20 | 21 | 22 | {{ t }} 23 | 24 | 25 | {% endfor %} 26 |

27 | {% endif %} 28 |
29 | 47 | 48 | {% endblock %} 49 | -------------------------------------------------------------------------------- /content/soybean/contents.lr: -------------------------------------------------------------------------------- 1 | name: Soybean 2 | --- 3 | description: 4 | 5 | Michalski's famous soybean disease database. 6 | 7 | ### 19 Classes 8 | diaporthe-stem-canker, charcoal-rot, rhizoctonia-root-rot, 9 | phytophthora-rot, brown-stem-rot, powdery-mildew, 10 | downy-mildew, brown-spot, bacterial-blight, 11 | bacterial-pustule, purple-seed-stain, anthracnose, 12 | phyllosticta-leaf-spot, alternarialeaf-spot, 13 | frog-eye-leaf-spot, diaporthe-pod-&-stem-blight, 14 | cyst-nematode, 2-4-d-injury, herbicide-injury. 15 | 16 | ### Attributes 17 | 1. date: april,may,june,july,august,september,october,?. 18 | 2. plant-stand: normal,lt-normal,?. 19 | 3. precip: lt-norm,norm,gt-norm,?. 20 | 4. temp: lt-norm,norm,gt-norm,?. 21 | 5. hail: yes,no,?. 22 | 6. crop-hist: diff-lst-year,same-lst-yr,same-lst-two-yrs, 23 | same-lst-sev-yrs,?. 24 | 7. area-damaged: scattered,low-areas,upper-areas,whole-field,?. 25 | 8. severity: minor,pot-severe,severe,?. 26 | 9. seed-tmt: none,fungicide,other,?. 27 | 10. germination: 90-100%,80-89%,lt-80%,?. 28 | 11. plant-growth: norm,abnorm,?. 29 | 12. leaves: norm,abnorm. 30 | 13. leafspots-halo: absent,yellow-halos,no-yellow-halos,?. 31 | 14. leafspots-marg: w-s-marg,no-w-s-marg,dna,?. 32 | 15. leafspot-size: lt-1/8,gt-1/8,dna,?. 33 | 16. leaf-shread: absent,present,?. 34 | 17. leaf-malf: absent,present,?. 35 | 18. leaf-mild: absent,upper-surf,lower-surf,?. 36 | 19. stem: norm,abnorm,?. 37 | 20. lodging: yes,no,?. 38 | 21. stem-cankers: absent,below-soil,above-soil,above-sec-nde,?. 39 | 22. canker-lesion: dna,brown,dk-brown-blk,tan,?. 40 | 23. fruiting-bodies: absent,present,?. 41 | 24. external decay: absent,firm-and-dry,watery,?. 42 | 25. mycelium: absent,present,?. 43 | 26. int-discolor: none,brown,black,?. 44 | 27. sclerotia: absent,present,?. 45 | 28. fruit-pods: norm,diseased,few-present,dna,?. 46 | 29. fruit spots: absent,colored,brown-w/blk-specks,distort,dna,?. 47 | 30. seed: norm,abnorm,?. 48 | 31. mold-growth: absent,present,?. 49 | 32. seed-discolor: absent,present,?. 50 | 33. seed-size: norm,lt-norm,?. 51 | 34. shriveling: absent,present,?. 52 | 35. roots: norm,rotted,galls-cysts,?. 53 | --- 54 | license: Public Domain 55 | --- 56 | tags: classification 57 | --- 58 | upload_date: 2019-11-17 59 | --- 60 | attributes: 35 61 | --- 62 | instances: 683 63 | -------------------------------------------------------------------------------- /content/divorce/contents.lr: -------------------------------------------------------------------------------- 1 | name: Divorce 2 | --- 3 | attributes: 55 4 | --- 5 | description: 6 | 7 | Participants completed the Personal Information Form and Divorce Predictors Scale. 8 | 9 | ### Attributes 10 | 1. If one of us apologizes when our discussion deteriorates, the discussion ends. 11 | 2. I know we can ignore our differences, even if things get hard sometimes. 12 | 3. When we need it, we can take our discussions with my spouse from the beginning and correct it. 13 | 4. When I discuss with my spouse, to contact him will eventually work. 14 | 5. The time I spent with my wife is special for us. 15 | 6. We don't have time at home as partners. 16 | 7. We are like two strangers who share the same environment at home rather than family. 17 | 8. I enjoy our holidays with my wife. 18 | 9. I enjoy traveling with my wife. 19 | 10. Most of our goals are common to my spouse. 20 | 11. I think that one day in the future, when I look back, I see that my spouse and I have been in harmony with each other. 21 | 12. My spouse and I have similar values in terms of personal freedom. 22 | 13. My spouse and I have similar sense of entertainment. 23 | 14. Most of our goals for people (children, friends, etc.) are the same. 24 | 15. Our dreams with my spouse are similar and harmonious. 25 | 16. We're compatible with my spouse about what love should be. 26 | 17. We share the same views about being happy in our life with my spouse 27 | 18. My spouse and I have similar ideas about how marriage should be 28 | 19. My spouse and I have similar ideas about how roles should be in marriage 29 | 20. My spouse and I have similar values in trust. 30 | 21. I know exactly what my wife likes. 31 | 22. I know how my spouse wants to be taken care of when she/he sick. 32 | 23. I know my spouse's favorite food. 33 | 24. I can tell you what kind of stress my spouse is facing in her/his life. 34 | 25. I have knowledge of my spouse's inner world. 35 | 26. I know my spouse's basic anxieties. 36 | 27. I know what my spouse's current sources of stress are. 37 | 28. I know my spouse's hopes and wishes. 38 | 29. I know my spouse very well. 39 | 30. I know my spouse's friends and their social relationships. 40 | 31. I feel aggressive when I argue with my spouse. 41 | 32. When discussing with my spouse, I usually use expressions such as ‘you always’ or ‘you never’ . 42 | 33. I can use negative statements about my spouse's personality during our discussions. 43 | 34. I can use offensive expressions during our discussions. 44 | 35. I can insult my spouse during our discussions. 45 | 36. I can be humiliating when we discussions. 46 | 37. My discussion with my spouse is not calm. 47 | 38. I hate my spouse's way of open a subject. 48 | 39. Our discussions often occur suddenly. 49 | 40. We're just starting a discussion before I know what's going on. 50 | 41. When I talk to my spouse about something, my calm suddenly breaks. 51 | 42. When I argue with my spouse, ı only go out and I don't say a word. 52 | 43. I mostly stay silent to calm the environment a little bit. 53 | 44. Sometimes I think it's good for me to leave home for a while. 54 | 45. I'd rather stay silent than discuss with my spouse. 55 | 46. Even if I'm right in the discussion, I stay silent to hurt my spouse. 56 | 47. When I discuss with my spouse, I stay silent because I am afraid of not being able to control my anger. 57 | 48. I feel right in our discussions. 58 | 49. I have nothing to do with what I've been accused of. 59 | 50. I'm not actually the one who's guilty about what I'm accused of. 60 | 51. I'm not the one who's wrong about problems at home. 61 | 52. I wouldn't hesitate to tell my spouse about her/his inadequacy. 62 | 53. When I discuss, I remind my spouse of her/his inadequacy. 63 | 54. I'm not afraid to tell my spouse about her/his incompetence. 64 | --- 65 | instances: 170 66 | --- 67 | license: Public Domain 68 | --- 69 | tags: classification 70 | -------------------------------------------------------------------------------- /content/labor/labor.csv: -------------------------------------------------------------------------------- 1 | duration,wage-increase-first-year,wage-increase-second-year,wage-increase-third-year,cost-of-living-adjustment,working-hours,pension,standby-pay,shift-differential,education-allowance,statutory-holidays,vacation,longterm-disability-assistance,contribution-to-dental-plan,bereavement-assistance,contribution-to-health-plan,class 2 | 1,5,?,?,?,40,?,?,2,?,11,average,?,?,yes,?,good 3 | 2,4.5,5.8,?,?,35,ret_allw,?,?,yes,11,below_average,?,full,?,full,good 4 | ?,?,?,?,?,38,empl_contr,?,5,?,11,generous,yes,half,yes,half,good 5 | 3,3.7,4,5,tc,?,?,?,?,yes,?,?,?,?,yes,?,good 6 | 3,4.5,4.5,5,?,40,?,?,?,?,12,average,?,half,yes,half,good 7 | 2,2,2.5,?,?,35,?,?,6,yes,12,average,?,?,?,?,good 8 | 3,4,5,5,tc,?,empl_contr,?,?,?,12,generous,yes,none,yes,half,good 9 | 3,6.9,4.8,2.3,?,40,?,?,3,?,12,below_average,?,?,?,?,good 10 | 2,3,7,?,?,38,?,12,25,yes,11,below_average,yes,half,yes,?,good 11 | 1,5.7,?,?,none,40,empl_contr,?,4,?,11,generous,yes,full,?,?,good 12 | 3,3.5,4,4.6,none,36,?,?,3,?,13,generous,?,?,yes,full,good 13 | 2,6.4,6.4,?,?,38,?,?,4,?,15,?,?,full,?,?,good 14 | 2,3.5,4,?,none,40,?,?,2,no,10,below_average,no,half,?,half,bad 15 | 3,3.5,4,5.1,tcf,37,?,?,4,?,13,generous,?,full,yes,full,good 16 | 1,3,?,?,none,36,?,?,10,no,11,generous,?,?,?,?,good 17 | 2,4.5,4,?,none,37,empl_contr,?,?,?,11,average,?,full,yes,?,good 18 | 1,2.8,?,?,?,35,?,?,2,?,12,below_average,?,?,?,?,good 19 | 1,2.1,?,?,tc,40,ret_allw,2,3,no,9,below_average,yes,half,?,none,bad 20 | 1,2,?,?,none,38,none,?,?,yes,11,average,no,none,no,none,bad 21 | 2,4,5,?,tcf,35,?,13,5,?,15,generous,?,?,?,?,good 22 | 2,4.3,4.4,?,?,38,?,?,4,?,12,generous,?,full,?,full,good 23 | 2,2.5,3,?,?,40,none,?,?,?,11,below_average,?,?,?,?,bad 24 | 3,3.5,4,4.6,tcf,27,?,?,?,?,?,?,?,?,?,?,good 25 | 2,4.5,4,?,?,40,?,?,4,?,10,generous,?,half,?,full,good 26 | 1,6,?,?,?,38,?,8,3,?,9,generous,?,?,?,?,good 27 | 3,2,2,2,none,40,none,?,?,?,10,below_average,?,half,yes,full,bad 28 | 2,4.5,4.5,?,tcf,?,?,?,?,yes,10,below_average,yes,none,?,half,good 29 | 2,3,3,?,none,33,?,?,?,yes,12,generous,?,?,yes,full,good 30 | 2,5,4,?,none,37,?,?,5,no,11,below_average,yes,full,yes,full,good 31 | 3,2,2.5,?,?,35,none,?,?,?,10,average,?,?,yes,full,bad 32 | 3,4.5,4.5,5,none,40,?,?,?,no,11,average,?,half,?,?,good 33 | 3,3,2,2.5,tc,40,none,?,5,no,10,below_average,yes,half,yes,full,bad 34 | 2,2.5,2.5,?,?,38,empl_contr,?,?,?,10,average,?,?,?,?,bad 35 | 2,4,5,?,none,40,none,?,3,no,10,below_average,no,none,?,none,bad 36 | 3,2,2.5,2.1,tc,40,none,2,1,no,10,below_average,no,half,yes,full,bad 37 | 2,2,2,?,none,40,none,?,?,no,11,average,yes,none,yes,full,bad 38 | 1,2,?,?,tc,40,ret_allw,4,0,no,11,generous,no,none,no,none,bad 39 | 1,2.8,?,?,none,38,empl_contr,2,3,no,9,below_average,yes,half,?,none,bad 40 | 3,2,2.5,2,?,37,empl_contr,?,?,?,10,average,?,?,yes,none,bad 41 | 2,4.5,4,?,none,40,?,?,4,?,12,average,yes,full,yes,half,good 42 | 1,4,?,?,none,?,none,?,?,yes,11,average,no,none,no,none,bad 43 | 2,2,3,?,none,38,empl_contr,?,?,yes,12,generous,yes,none,yes,full,bad 44 | 2,2.5,2.5,?,tc,39,empl_contr,?,?,?,12,average,?,?,yes,?,bad 45 | 2,2.5,3,?,tcf,40,none,?,?,?,11,below_average,?,?,yes,?,bad 46 | 2,4,4,?,none,40,none,?,3,?,10,below_average,no,none,?,none,bad 47 | 2,4.5,4,?,?,40,?,?,2,no,10,below_average,no,half,?,half,bad 48 | 2,4.5,4,?,none,40,?,?,5,?,11,average,?,full,yes,full,good 49 | 2,4.6,4.6,?,tcf,38,?,?,?,?,?,?,yes,half,?,half,good 50 | 2,5,4.5,?,none,38,?,14,5,?,11,below_average,yes,?,?,full,good 51 | 2,5.7,4.5,?,none,40,ret_allw,?,?,?,11,average,yes,full,yes,full,good 52 | 2,7,5.3,?,?,?,?,?,?,?,11,?,yes,full,?,?,good 53 | 3,2,3,?,tcf,?,empl_contr,?,?,yes,?,?,yes,half,yes,?,good 54 | 3,3.5,4,4.5,tcf,35,?,?,?,?,13,generous,?,?,yes,full,good 55 | 3,4,3.5,?,none,40,empl_contr,?,6,?,11,average,yes,full,?,full,good 56 | 3,5,4.4,?,none,38,empl_contr,10,6,?,11,generous,yes,?,?,full,good 57 | 3,5,5,5,?,40,?,?,?,?,12,average,?,half,yes,half,good 58 | 3,6,6,4,?,35,?,?,14,?,9,generous,yes,full,yes,full,good 59 | -------------------------------------------------------------------------------- /content/iris/iris.csv: -------------------------------------------------------------------------------- 1 | sepallength,sepalwidth,petallength,petalwidth,class 2 | 5.1,3.5,1.4,0.2,Iris-setosa 3 | 4.9,3,1.4,0.2,Iris-setosa 4 | 4.7,3.2,1.3,0.2,Iris-setosa 5 | 4.6,3.1,1.5,0.2,Iris-setosa 6 | 5,3.6,1.4,0.2,Iris-setosa 7 | 5.4,3.9,1.7,0.4,Iris-setosa 8 | 4.6,3.4,1.4,0.3,Iris-setosa 9 | 5,3.4,1.5,0.2,Iris-setosa 10 | 4.4,2.9,1.4,0.2,Iris-setosa 11 | 4.9,3.1,1.5,0.1,Iris-setosa 12 | 5.4,3.7,1.5,0.2,Iris-setosa 13 | 4.8,3.4,1.6,0.2,Iris-setosa 14 | 4.8,3,1.4,0.1,Iris-setosa 15 | 4.3,3,1.1,0.1,Iris-setosa 16 | 5.8,4,1.2,0.2,Iris-setosa 17 | 5.7,4.4,1.5,0.4,Iris-setosa 18 | 5.4,3.9,1.3,0.4,Iris-setosa 19 | 5.1,3.5,1.4,0.3,Iris-setosa 20 | 5.7,3.8,1.7,0.3,Iris-setosa 21 | 5.1,3.8,1.5,0.3,Iris-setosa 22 | 5.4,3.4,1.7,0.2,Iris-setosa 23 | 5.1,3.7,1.5,0.4,Iris-setosa 24 | 4.6,3.6,1,0.2,Iris-setosa 25 | 5.1,3.3,1.7,0.5,Iris-setosa 26 | 4.8,3.4,1.9,0.2,Iris-setosa 27 | 5,3,1.6,0.2,Iris-setosa 28 | 5,3.4,1.6,0.4,Iris-setosa 29 | 5.2,3.5,1.5,0.2,Iris-setosa 30 | 5.2,3.4,1.4,0.2,Iris-setosa 31 | 4.7,3.2,1.6,0.2,Iris-setosa 32 | 4.8,3.1,1.6,0.2,Iris-setosa 33 | 5.4,3.4,1.5,0.4,Iris-setosa 34 | 5.2,4.1,1.5,0.1,Iris-setosa 35 | 5.5,4.2,1.4,0.2,Iris-setosa 36 | 4.9,3.1,1.5,0.1,Iris-setosa 37 | 5,3.2,1.2,0.2,Iris-setosa 38 | 5.5,3.5,1.3,0.2,Iris-setosa 39 | 4.9,3.1,1.5,0.1,Iris-setosa 40 | 4.4,3,1.3,0.2,Iris-setosa 41 | 5.1,3.4,1.5,0.2,Iris-setosa 42 | 5,3.5,1.3,0.3,Iris-setosa 43 | 4.5,2.3,1.3,0.3,Iris-setosa 44 | 4.4,3.2,1.3,0.2,Iris-setosa 45 | 5,3.5,1.6,0.6,Iris-setosa 46 | 5.1,3.8,1.9,0.4,Iris-setosa 47 | 4.8,3,1.4,0.3,Iris-setosa 48 | 5.1,3.8,1.6,0.2,Iris-setosa 49 | 4.6,3.2,1.4,0.2,Iris-setosa 50 | 5.3,3.7,1.5,0.2,Iris-setosa 51 | 5,3.3,1.4,0.2,Iris-setosa 52 | 7,3.2,4.7,1.4,Iris-versicolor 53 | 6.4,3.2,4.5,1.5,Iris-versicolor 54 | 6.9,3.1,4.9,1.5,Iris-versicolor 55 | 5.5,2.3,4,1.3,Iris-versicolor 56 | 6.5,2.8,4.6,1.5,Iris-versicolor 57 | 5.7,2.8,4.5,1.3,Iris-versicolor 58 | 6.3,3.3,4.7,1.6,Iris-versicolor 59 | 4.9,2.4,3.3,1,Iris-versicolor 60 | 6.6,2.9,4.6,1.3,Iris-versicolor 61 | 5.2,2.7,3.9,1.4,Iris-versicolor 62 | 5,2,3.5,1,Iris-versicolor 63 | 5.9,3,4.2,1.5,Iris-versicolor 64 | 6,2.2,4,1,Iris-versicolor 65 | 6.1,2.9,4.7,1.4,Iris-versicolor 66 | 5.6,2.9,3.6,1.3,Iris-versicolor 67 | 6.7,3.1,4.4,1.4,Iris-versicolor 68 | 5.6,3,4.5,1.5,Iris-versicolor 69 | 5.8,2.7,4.1,1,Iris-versicolor 70 | 6.2,2.2,4.5,1.5,Iris-versicolor 71 | 5.6,2.5,3.9,1.1,Iris-versicolor 72 | 5.9,3.2,4.8,1.8,Iris-versicolor 73 | 6.1,2.8,4,1.3,Iris-versicolor 74 | 6.3,2.5,4.9,1.5,Iris-versicolor 75 | 6.1,2.8,4.7,1.2,Iris-versicolor 76 | 6.4,2.9,4.3,1.3,Iris-versicolor 77 | 6.6,3,4.4,1.4,Iris-versicolor 78 | 6.8,2.8,4.8,1.4,Iris-versicolor 79 | 6.7,3,5,1.7,Iris-versicolor 80 | 6,2.9,4.5,1.5,Iris-versicolor 81 | 5.7,2.6,3.5,1,Iris-versicolor 82 | 5.5,2.4,3.8,1.1,Iris-versicolor 83 | 5.5,2.4,3.7,1,Iris-versicolor 84 | 5.8,2.7,3.9,1.2,Iris-versicolor 85 | 6,2.7,5.1,1.6,Iris-versicolor 86 | 5.4,3,4.5,1.5,Iris-versicolor 87 | 6,3.4,4.5,1.6,Iris-versicolor 88 | 6.7,3.1,4.7,1.5,Iris-versicolor 89 | 6.3,2.3,4.4,1.3,Iris-versicolor 90 | 5.6,3,4.1,1.3,Iris-versicolor 91 | 5.5,2.5,4,1.3,Iris-versicolor 92 | 5.5,2.6,4.4,1.2,Iris-versicolor 93 | 6.1,3,4.6,1.4,Iris-versicolor 94 | 5.8,2.6,4,1.2,Iris-versicolor 95 | 5,2.3,3.3,1,Iris-versicolor 96 | 5.6,2.7,4.2,1.3,Iris-versicolor 97 | 5.7,3,4.2,1.2,Iris-versicolor 98 | 5.7,2.9,4.2,1.3,Iris-versicolor 99 | 6.2,2.9,4.3,1.3,Iris-versicolor 100 | 5.1,2.5,3,1.1,Iris-versicolor 101 | 5.7,2.8,4.1,1.3,Iris-versicolor 102 | 6.3,3.3,6,2.5,Iris-virginica 103 | 5.8,2.7,5.1,1.9,Iris-virginica 104 | 7.1,3,5.9,2.1,Iris-virginica 105 | 6.3,2.9,5.6,1.8,Iris-virginica 106 | 6.5,3,5.8,2.2,Iris-virginica 107 | 7.6,3,6.6,2.1,Iris-virginica 108 | 4.9,2.5,4.5,1.7,Iris-virginica 109 | 7.3,2.9,6.3,1.8,Iris-virginica 110 | 6.7,2.5,5.8,1.8,Iris-virginica 111 | 7.2,3.6,6.1,2.5,Iris-virginica 112 | 6.5,3.2,5.1,2,Iris-virginica 113 | 6.4,2.7,5.3,1.9,Iris-virginica 114 | 6.8,3,5.5,2.1,Iris-virginica 115 | 5.7,2.5,5,2,Iris-virginica 116 | 5.8,2.8,5.1,2.4,Iris-virginica 117 | 6.4,3.2,5.3,2.3,Iris-virginica 118 | 6.5,3,5.5,1.8,Iris-virginica 119 | 7.7,3.8,6.7,2.2,Iris-virginica 120 | 7.7,2.6,6.9,2.3,Iris-virginica 121 | 6,2.2,5,1.5,Iris-virginica 122 | 6.9,3.2,5.7,2.3,Iris-virginica 123 | 5.6,2.8,4.9,2,Iris-virginica 124 | 7.7,2.8,6.7,2,Iris-virginica 125 | 6.3,2.7,4.9,1.8,Iris-virginica 126 | 6.7,3.3,5.7,2.1,Iris-virginica 127 | 7.2,3.2,6,1.8,Iris-virginica 128 | 6.2,2.8,4.8,1.8,Iris-virginica 129 | 6.1,3,4.9,1.8,Iris-virginica 130 | 6.4,2.8,5.6,2.1,Iris-virginica 131 | 7.2,3,5.8,1.6,Iris-virginica 132 | 7.4,2.8,6.1,1.9,Iris-virginica 133 | 7.9,3.8,6.4,2,Iris-virginica 134 | 6.4,2.8,5.6,2.2,Iris-virginica 135 | 6.3,2.8,5.1,1.5,Iris-virginica 136 | 6.1,2.6,5.6,1.4,Iris-virginica 137 | 7.7,3,6.1,2.3,Iris-virginica 138 | 6.3,3.4,5.6,2.4,Iris-virginica 139 | 6.4,3.1,5.5,1.8,Iris-virginica 140 | 6,3,4.8,1.8,Iris-virginica 141 | 6.9,3.1,5.4,2.1,Iris-virginica 142 | 6.7,3.1,5.6,2.4,Iris-virginica 143 | 6.9,3.1,5.1,2.3,Iris-virginica 144 | 5.8,2.7,5.1,1.9,Iris-virginica 145 | 6.8,3.2,5.9,2.3,Iris-virginica 146 | 6.7,3.3,5.7,2.5,Iris-virginica 147 | 6.7,3,5.2,2.3,Iris-virginica 148 | 6.3,2.5,5,1.9,Iris-virginica 149 | 6.5,3,5.2,2,Iris-virginica 150 | 6.2,3.4,5.4,2.3,Iris-virginica 151 | 5.9,3,5.1,1.8,Iris-virginica 152 | -------------------------------------------------------------------------------- /content/iris/iris.arff: -------------------------------------------------------------------------------- 1 | % 1. Title: Iris Plants Database 2 | % 3 | % 2. Sources: 4 | % (a) Creator: R.A. Fisher 5 | % (b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov) 6 | % (c) Date: July, 1988 7 | % 8 | % 3. Past Usage: 9 | % - Publications: too many to mention!!! Here are a few. 10 | % 1. Fisher,R.A. "The use of multiple measurements in taxonomic problems" 11 | % Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions 12 | % to Mathematical Statistics" (John Wiley, NY, 1950). 13 | % 2. Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis. 14 | % (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218. 15 | % 3. Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System 16 | % Structure and Classification Rule for Recognition in Partially Exposed 17 | % Environments". IEEE Transactions on Pattern Analysis and Machine 18 | % Intelligence, Vol. PAMI-2, No. 1, 67-71. 19 | % -- Results: 20 | % -- very low misclassification rates (0% for the setosa class) 21 | % 4. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE 22 | % Transactions on Information Theory, May 1972, 431-433. 23 | % -- Results: 24 | % -- very low misclassification rates again 25 | % 5. See also: 1988 MLC Proceedings, 54-64. Cheeseman et al's AUTOCLASS II 26 | % conceptual clustering system finds 3 classes in the data. 27 | % 28 | % 4. Relevant Information: 29 | % --- This is perhaps the best known database to be found in the pattern 30 | % recognition literature. Fisher's paper is a classic in the field 31 | % and is referenced frequently to this day. (See Duda & Hart, for 32 | % example.) The data set contains 3 classes of 50 instances each, 33 | % where each class refers to a type of iris plant. One class is 34 | % linearly separable from the other 2; the latter are NOT linearly 35 | % separable from each other. 36 | % --- Predicted attribute: class of iris plant. 37 | % --- This is an exceedingly simple domain. 38 | % 39 | % 5. Number of Instances: 150 (50 in each of three classes) 40 | % 41 | % 6. Number of Attributes: 4 numeric, predictive attributes and the class 42 | % 43 | % 7. Attribute Information: 44 | % 1. sepal length in cm 45 | % 2. sepal width in cm 46 | % 3. petal length in cm 47 | % 4. petal width in cm 48 | % 5. class: 49 | % -- Iris Setosa 50 | % -- Iris Versicolour 51 | % -- Iris Virginica 52 | % 53 | % 8. Missing Attribute Values: None 54 | % 55 | % Summary Statistics: 56 | % Min Max Mean SD Class Correlation 57 | % sepal length: 4.3 7.9 5.84 0.83 0.7826 58 | % sepal width: 2.0 4.4 3.05 0.43 -0.4194 59 | % petal length: 1.0 6.9 3.76 1.76 0.9490 (high!) 60 | % petal width: 0.1 2.5 1.20 0.76 0.9565 (high!) 61 | % 62 | % 9. Class Distribution: 33.3% for each of 3 classes. 63 | 64 | @RELATION iris 65 | 66 | @ATTRIBUTE sepallength REAL 67 | @ATTRIBUTE sepalwidth REAL 68 | @ATTRIBUTE petallength REAL 69 | @ATTRIBUTE petalwidth REAL 70 | @ATTRIBUTE class {Iris-setosa,Iris-versicolor,Iris-virginica} 71 | 72 | @DATA 73 | 5.1,3.5,1.4,0.2,Iris-setosa 74 | 4.9,3.0,1.4,0.2,Iris-setosa 75 | 4.7,3.2,1.3,0.2,Iris-setosa 76 | 4.6,3.1,1.5,0.2,Iris-setosa 77 | 5.0,3.6,1.4,0.2,Iris-setosa 78 | 5.4,3.9,1.7,0.4,Iris-setosa 79 | 4.6,3.4,1.4,0.3,Iris-setosa 80 | 5.0,3.4,1.5,0.2,Iris-setosa 81 | 4.4,2.9,1.4,0.2,Iris-setosa 82 | 4.9,3.1,1.5,0.1,Iris-setosa 83 | 5.4,3.7,1.5,0.2,Iris-setosa 84 | 4.8,3.4,1.6,0.2,Iris-setosa 85 | 4.8,3.0,1.4,0.1,Iris-setosa 86 | 4.3,3.0,1.1,0.1,Iris-setosa 87 | 5.8,4.0,1.2,0.2,Iris-setosa 88 | 5.7,4.4,1.5,0.4,Iris-setosa 89 | 5.4,3.9,1.3,0.4,Iris-setosa 90 | 5.1,3.5,1.4,0.3,Iris-setosa 91 | 5.7,3.8,1.7,0.3,Iris-setosa 92 | 5.1,3.8,1.5,0.3,Iris-setosa 93 | 5.4,3.4,1.7,0.2,Iris-setosa 94 | 5.1,3.7,1.5,0.4,Iris-setosa 95 | 4.6,3.6,1.0,0.2,Iris-setosa 96 | 5.1,3.3,1.7,0.5,Iris-setosa 97 | 4.8,3.4,1.9,0.2,Iris-setosa 98 | 5.0,3.0,1.6,0.2,Iris-setosa 99 | 5.0,3.4,1.6,0.4,Iris-setosa 100 | 5.2,3.5,1.5,0.2,Iris-setosa 101 | 5.2,3.4,1.4,0.2,Iris-setosa 102 | 4.7,3.2,1.6,0.2,Iris-setosa 103 | 4.8,3.1,1.6,0.2,Iris-setosa 104 | 5.4,3.4,1.5,0.4,Iris-setosa 105 | 5.2,4.1,1.5,0.1,Iris-setosa 106 | 5.5,4.2,1.4,0.2,Iris-setosa 107 | 4.9,3.1,1.5,0.1,Iris-setosa 108 | 5.0,3.2,1.2,0.2,Iris-setosa 109 | 5.5,3.5,1.3,0.2,Iris-setosa 110 | 4.9,3.1,1.5,0.1,Iris-setosa 111 | 4.4,3.0,1.3,0.2,Iris-setosa 112 | 5.1,3.4,1.5,0.2,Iris-setosa 113 | 5.0,3.5,1.3,0.3,Iris-setosa 114 | 4.5,2.3,1.3,0.3,Iris-setosa 115 | 4.4,3.2,1.3,0.2,Iris-setosa 116 | 5.0,3.5,1.6,0.6,Iris-setosa 117 | 5.1,3.8,1.9,0.4,Iris-setosa 118 | 4.8,3.0,1.4,0.3,Iris-setosa 119 | 5.1,3.8,1.6,0.2,Iris-setosa 120 | 4.6,3.2,1.4,0.2,Iris-setosa 121 | 5.3,3.7,1.5,0.2,Iris-setosa 122 | 5.0,3.3,1.4,0.2,Iris-setosa 123 | 7.0,3.2,4.7,1.4,Iris-versicolor 124 | 6.4,3.2,4.5,1.5,Iris-versicolor 125 | 6.9,3.1,4.9,1.5,Iris-versicolor 126 | 5.5,2.3,4.0,1.3,Iris-versicolor 127 | 6.5,2.8,4.6,1.5,Iris-versicolor 128 | 5.7,2.8,4.5,1.3,Iris-versicolor 129 | 6.3,3.3,4.7,1.6,Iris-versicolor 130 | 4.9,2.4,3.3,1.0,Iris-versicolor 131 | 6.6,2.9,4.6,1.3,Iris-versicolor 132 | 5.2,2.7,3.9,1.4,Iris-versicolor 133 | 5.0,2.0,3.5,1.0,Iris-versicolor 134 | 5.9,3.0,4.2,1.5,Iris-versicolor 135 | 6.0,2.2,4.0,1.0,Iris-versicolor 136 | 6.1,2.9,4.7,1.4,Iris-versicolor 137 | 5.6,2.9,3.6,1.3,Iris-versicolor 138 | 6.7,3.1,4.4,1.4,Iris-versicolor 139 | 5.6,3.0,4.5,1.5,Iris-versicolor 140 | 5.8,2.7,4.1,1.0,Iris-versicolor 141 | 6.2,2.2,4.5,1.5,Iris-versicolor 142 | 5.6,2.5,3.9,1.1,Iris-versicolor 143 | 5.9,3.2,4.8,1.8,Iris-versicolor 144 | 6.1,2.8,4.0,1.3,Iris-versicolor 145 | 6.3,2.5,4.9,1.5,Iris-versicolor 146 | 6.1,2.8,4.7,1.2,Iris-versicolor 147 | 6.4,2.9,4.3,1.3,Iris-versicolor 148 | 6.6,3.0,4.4,1.4,Iris-versicolor 149 | 6.8,2.8,4.8,1.4,Iris-versicolor 150 | 6.7,3.0,5.0,1.7,Iris-versicolor 151 | 6.0,2.9,4.5,1.5,Iris-versicolor 152 | 5.7,2.6,3.5,1.0,Iris-versicolor 153 | 5.5,2.4,3.8,1.1,Iris-versicolor 154 | 5.5,2.4,3.7,1.0,Iris-versicolor 155 | 5.8,2.7,3.9,1.2,Iris-versicolor 156 | 6.0,2.7,5.1,1.6,Iris-versicolor 157 | 5.4,3.0,4.5,1.5,Iris-versicolor 158 | 6.0,3.4,4.5,1.6,Iris-versicolor 159 | 6.7,3.1,4.7,1.5,Iris-versicolor 160 | 6.3,2.3,4.4,1.3,Iris-versicolor 161 | 5.6,3.0,4.1,1.3,Iris-versicolor 162 | 5.5,2.5,4.0,1.3,Iris-versicolor 163 | 5.5,2.6,4.4,1.2,Iris-versicolor 164 | 6.1,3.0,4.6,1.4,Iris-versicolor 165 | 5.8,2.6,4.0,1.2,Iris-versicolor 166 | 5.0,2.3,3.3,1.0,Iris-versicolor 167 | 5.6,2.7,4.2,1.3,Iris-versicolor 168 | 5.7,3.0,4.2,1.2,Iris-versicolor 169 | 5.7,2.9,4.2,1.3,Iris-versicolor 170 | 6.2,2.9,4.3,1.3,Iris-versicolor 171 | 5.1,2.5,3.0,1.1,Iris-versicolor 172 | 5.7,2.8,4.1,1.3,Iris-versicolor 173 | 6.3,3.3,6.0,2.5,Iris-virginica 174 | 5.8,2.7,5.1,1.9,Iris-virginica 175 | 7.1,3.0,5.9,2.1,Iris-virginica 176 | 6.3,2.9,5.6,1.8,Iris-virginica 177 | 6.5,3.0,5.8,2.2,Iris-virginica 178 | 7.6,3.0,6.6,2.1,Iris-virginica 179 | 4.9,2.5,4.5,1.7,Iris-virginica 180 | 7.3,2.9,6.3,1.8,Iris-virginica 181 | 6.7,2.5,5.8,1.8,Iris-virginica 182 | 7.2,3.6,6.1,2.5,Iris-virginica 183 | 6.5,3.2,5.1,2.0,Iris-virginica 184 | 6.4,2.7,5.3,1.9,Iris-virginica 185 | 6.8,3.0,5.5,2.1,Iris-virginica 186 | 5.7,2.5,5.0,2.0,Iris-virginica 187 | 5.8,2.8,5.1,2.4,Iris-virginica 188 | 6.4,3.2,5.3,2.3,Iris-virginica 189 | 6.5,3.0,5.5,1.8,Iris-virginica 190 | 7.7,3.8,6.7,2.2,Iris-virginica 191 | 7.7,2.6,6.9,2.3,Iris-virginica 192 | 6.0,2.2,5.0,1.5,Iris-virginica 193 | 6.9,3.2,5.7,2.3,Iris-virginica 194 | 5.6,2.8,4.9,2.0,Iris-virginica 195 | 7.7,2.8,6.7,2.0,Iris-virginica 196 | 6.3,2.7,4.9,1.8,Iris-virginica 197 | 6.7,3.3,5.7,2.1,Iris-virginica 198 | 7.2,3.2,6.0,1.8,Iris-virginica 199 | 6.2,2.8,4.8,1.8,Iris-virginica 200 | 6.1,3.0,4.9,1.8,Iris-virginica 201 | 6.4,2.8,5.6,2.1,Iris-virginica 202 | 7.2,3.0,5.8,1.6,Iris-virginica 203 | 7.4,2.8,6.1,1.9,Iris-virginica 204 | 7.9,3.8,6.4,2.0,Iris-virginica 205 | 6.4,2.8,5.6,2.2,Iris-virginica 206 | 6.3,2.8,5.1,1.5,Iris-virginica 207 | 6.1,2.6,5.6,1.4,Iris-virginica 208 | 7.7,3.0,6.1,2.3,Iris-virginica 209 | 6.3,3.4,5.6,2.4,Iris-virginica 210 | 6.4,3.1,5.5,1.8,Iris-virginica 211 | 6.0,3.0,4.8,1.8,Iris-virginica 212 | 6.9,3.1,5.4,2.1,Iris-virginica 213 | 6.7,3.1,5.6,2.4,Iris-virginica 214 | 6.9,3.1,5.1,2.3,Iris-virginica 215 | 5.8,2.7,5.1,1.9,Iris-virginica 216 | 6.8,3.2,5.9,2.3,Iris-virginica 217 | 6.7,3.3,5.7,2.5,Iris-virginica 218 | 6.7,3.0,5.2,2.3,Iris-virginica 219 | 6.3,2.5,5.0,1.9,Iris-virginica 220 | 6.5,3.0,5.2,2.0,Iris-virginica 221 | 6.2,3.4,5.4,2.3,Iris-virginica 222 | 5.9,3.0,5.1,1.8,Iris-virginica 223 | % 224 | % 225 | % 226 | -------------------------------------------------------------------------------- /content/labor/labor.arff: -------------------------------------------------------------------------------- 1 | % Date: Tue, 15 Nov 88 15:44:08 EST 2 | % From: stan 3 | % To: aha@ICS.UCI.EDU 4 | % 5 | % 1. Title: Final settlements in labor negotitions in Canadian industry 6 | % 7 | % 2. Source Information 8 | % -- Creators: Collective Barganing Review, montly publication, 9 | % Labour Canada, Industrial Relations Information Service, 10 | % Ottawa, Ontario, K1A 0J2, Canada, (819) 997-3117 11 | % The data includes all collective agreements reached 12 | % in the business and personal services sector for locals 13 | % with at least 500 members (teachers, nurses, university 14 | % staff, police, etc) in Canada in 87 and first quarter of 88. 15 | % -- Donor: Stan Matwin, Computer Science Dept, University of Ottawa, 16 | % 34 Somerset East, K1N 9B4, (stan@uotcsi2.bitnet) 17 | % -- Date: November 1988 18 | % 19 | % 3. Past Usage: 20 | % -- testing concept learning software, in particular 21 | % an experimental method to learn two-tiered concept descriptions. 22 | % The data was used to learn the description of an acceptable 23 | % and unacceptable contract. 24 | % The unacceptable contracts were either obtained by interviewing 25 | % experts, or by inventing near misses. 26 | % Examples of use are described in: 27 | % Bergadano, F., Matwin, S., Michalski, R., 28 | % Zhang, J., Measuring Quality of Concept Descriptions, 29 | % Procs. of the 3rd European Working Sessions on Learning, 30 | % Glasgow, October 1988. 31 | % Bergadano, F., Matwin, S., Michalski, R., Zhang, J., 32 | % Representing and Acquiring Imprecise and Context-dependent 33 | % Concepts in Knowledge-based Systems, Procs. of ISMIS'88, 34 | % North Holland, 1988. 35 | % 4. Relevant Information: 36 | % -- data was used to test 2tier approach with learning 37 | % from positive and negative examples 38 | % 39 | % 5. Number of Instances: 57 40 | % 41 | % 6. Number of Attributes: 16 42 | % 43 | % 7. Attribute Information: 44 | % 1. dur: duration of agreement 45 | % [1..7] 46 | % 2 wage1.wage : wage increase in first year of contract 47 | % [2.0 .. 7.0] 48 | % 3 wage2.wage : wage increase in second year of contract 49 | % [2.0 .. 7.0] 50 | % 4 wage3.wage : wage increase in third year of contract 51 | % [2.0 .. 7.0] 52 | % 5 cola : cost of living allowance 53 | % [none, tcf, tc] 54 | % 6 hours.hrs : number of working hours during week 55 | % [35 .. 40] 56 | % 7 pension : employer contributions to pension plan 57 | % [none, ret_allw, empl_contr] 58 | % 8 stby_pay : standby pay 59 | % [2 .. 25] 60 | % 9 shift_diff : shift differencial : supplement for work on II and III shift 61 | % [1 .. 25] 62 | % 10 educ_allw.boolean : education allowance 63 | % [true false] 64 | % 11 holidays : number of statutory holidays 65 | % [9 .. 15] 66 | % 12 vacation : number of paid vacation days 67 | % [ba, avg, gnr] 68 | % 13 lngtrm_disabil.boolean : 69 | % employer's help during employee longterm disabil 70 | % ity [true , false] 71 | % 14 dntl_ins : employers contribution towards the dental plan 72 | % [none, half, full] 73 | % 15 bereavement.boolean : employer's financial contribution towards the 74 | % covering the costs of bereavement 75 | % [true , false] 76 | % 16 empl_hplan : employer's contribution towards the health plan 77 | % [none, half, full] 78 | % 79 | % 8. Missing Attribute Values: None 80 | % 81 | % 9. Class Distribution: 82 | % 83 | % 10. Exceptions from format instructions: no commas between attribute values. 84 | % 85 | % 86 | @relation 'labor-neg-data' 87 | @attribute 'duration' real 88 | @attribute 'wage-increase-first-year' real 89 | @attribute 'wage-increase-second-year' real 90 | @attribute 'wage-increase-third-year' real 91 | @attribute 'cost-of-living-adjustment' {'none','tcf','tc'} 92 | @attribute 'working-hours' real 93 | @attribute 'pension' {'none','ret_allw','empl_contr'} 94 | @attribute 'standby-pay' real 95 | @attribute 'shift-differential' real 96 | @attribute 'education-allowance' {'yes','no'} 97 | @attribute 'statutory-holidays' real 98 | @attribute 'vacation' {'below_average','average','generous'} 99 | @attribute 'longterm-disability-assistance' {'yes','no'} 100 | @attribute 'contribution-to-dental-plan' {'none','half','full'} 101 | @attribute 'bereavement-assistance' {'yes','no'} 102 | @attribute 'contribution-to-health-plan' {'none','half','full'} 103 | @attribute 'class' {'bad','good'} 104 | @data 105 | 1,5,?,?,?,40,?,?,2,?,11,'average',?,?,'yes',?,'good' 106 | 2,4.5,5.8,?,?,35,'ret_allw',?,?,'yes',11,'below_average',?,'full',?,'full','good' 107 | ?,?,?,?,?,38,'empl_contr',?,5,?,11,'generous','yes','half','yes','half','good' 108 | 3,3.7,4,5,'tc',?,?,?,?,'yes',?,?,?,?,'yes',?,'good' 109 | 3,4.5,4.5,5,?,40,?,?,?,?,12,'average',?,'half','yes','half','good' 110 | 2,2,2.5,?,?,35,?,?,6,'yes',12,'average',?,?,?,?,'good' 111 | 3,4,5,5,'tc',?,'empl_contr',?,?,?,12,'generous','yes','none','yes','half','good' 112 | 3,6.9,4.8,2.3,?,40,?,?,3,?,12,'below_average',?,?,?,?,'good' 113 | 2,3,7,?,?,38,?,12,25,'yes',11,'below_average','yes','half','yes',?,'good' 114 | 1,5.7,?,?,'none',40,'empl_contr',?,4,?,11,'generous','yes','full',?,?,'good' 115 | 3,3.5,4,4.6,'none',36,?,?,3,?,13,'generous',?,?,'yes','full','good' 116 | 2,6.4,6.4,?,?,38,?,?,4,?,15,?,?,'full',?,?,'good' 117 | 2,3.5,4,?,'none',40,?,?,2,'no',10,'below_average','no','half',?,'half','bad' 118 | 3,3.5,4,5.1,'tcf',37,?,?,4,?,13,'generous',?,'full','yes','full','good' 119 | 1,3,?,?,'none',36,?,?,10,'no',11,'generous',?,?,?,?,'good' 120 | 2,4.5,4,?,'none',37,'empl_contr',?,?,?,11,'average',?,'full','yes',?,'good' 121 | 1,2.8,?,?,?,35,?,?,2,?,12,'below_average',?,?,?,?,'good' 122 | 1,2.1,?,?,'tc',40,'ret_allw',2,3,'no',9,'below_average','yes','half',?,'none','bad' 123 | 1,2,?,?,'none',38,'none',?,?,'yes',11,'average','no','none','no','none','bad' 124 | 2,4,5,?,'tcf',35,?,13,5,?,15,'generous',?,?,?,?,'good' 125 | 2,4.3,4.4,?,?,38,?,?,4,?,12,'generous',?,'full',?,'full','good' 126 | 2,2.5,3,?,?,40,'none',?,?,?,11,'below_average',?,?,?,?,'bad' 127 | 3,3.5,4,4.6,'tcf',27,?,?,?,?,?,?,?,?,?,?,'good' 128 | 2,4.5,4,?,?,40,?,?,4,?,10,'generous',?,'half',?,'full','good' 129 | 1,6,?,?,?,38,?,8,3,?,9,'generous',?,?,?,?,'good' 130 | 3,2,2,2,'none',40,'none',?,?,?,10,'below_average',?,'half','yes','full','bad' 131 | 2,4.5,4.5,?,'tcf',?,?,?,?,'yes',10,'below_average','yes','none',?,'half','good' 132 | 2,3,3,?,'none',33,?,?,?,'yes',12,'generous',?,?,'yes','full','good' 133 | 2,5,4,?,'none',37,?,?,5,'no',11,'below_average','yes','full','yes','full','good' 134 | 3,2,2.5,?,?,35,'none',?,?,?,10,'average',?,?,'yes','full','bad' 135 | 3,4.5,4.5,5,'none',40,?,?,?,'no',11,'average',?,'half',?,?,'good' 136 | 3,3,2,2.5,'tc',40,'none',?,5,'no',10,'below_average','yes','half','yes','full','bad' 137 | 2,2.5,2.5,?,?,38,'empl_contr',?,?,?,10,'average',?,?,?,?,'bad' 138 | 2,4,5,?,'none',40,'none',?,3,'no',10,'below_average','no','none',?,'none','bad' 139 | 3,2,2.5,2.1,'tc',40,'none',2,1,'no',10,'below_average','no','half','yes','full','bad' 140 | 2,2,2,?,'none',40,'none',?,?,'no',11,'average','yes','none','yes','full','bad' 141 | 1,2,?,?,'tc',40,'ret_allw',4,0,'no',11,'generous','no','none','no','none','bad' 142 | 1,2.8,?,?,'none',38,'empl_contr',2,3,'no',9,'below_average','yes','half',?,'none','bad' 143 | 3,2,2.5,2,?,37,'empl_contr',?,?,?,10,'average',?,?,'yes','none','bad' 144 | 2,4.5,4,?,'none',40,?,?,4,?,12,'average','yes','full','yes','half','good' 145 | 1,4,?,?,'none',?,'none',?,?,'yes',11,'average','no','none','no','none','bad' 146 | 2,2,3,?,'none',38,'empl_contr',?,?,'yes',12,'generous','yes','none','yes','full','bad' 147 | 2,2.5,2.5,?,'tc',39,'empl_contr',?,?,?,12,'average',?,?,'yes',?,'bad' 148 | 2,2.5,3,?,'tcf',40,'none',?,?,?,11,'below_average',?,?,'yes',?,'bad' 149 | 2,4,4,?,'none',40,'none',?,3,?,10,'below_average','no','none',?,'none','bad' 150 | 2,4.5,4,?,?,40,?,?,2,'no',10,'below_average','no','half',?,'half','bad' 151 | 2,4.5,4,?,'none',40,?,?,5,?,11,'average',?,'full','yes','full','good' 152 | 2,4.6,4.6,?,'tcf',38,?,?,?,?,?,?,'yes','half',?,'half','good' 153 | 2,5,4.5,?,'none',38,?,14,5,?,11,'below_average','yes',?,?,'full','good' 154 | 2,5.7,4.5,?,'none',40,'ret_allw',?,?,?,11,'average','yes','full','yes','full','good' 155 | 2,7,5.3,?,?,?,?,?,?,?,11,?,'yes','full',?,?,'good' 156 | 3,2,3,?,'tcf',?,'empl_contr',?,?,'yes',?,?,'yes','half','yes',?,'good' 157 | 3,3.5,4,4.5,'tcf',35,?,?,?,?,13,'generous',?,?,'yes','full','good' 158 | 3,4,3.5,?,'none',40,'empl_contr',?,6,?,11,'average','yes','full',?,'full','good' 159 | 3,5,4.4,?,'none',38,'empl_contr',10,6,?,11,'generous','yes',?,?,'full','good' 160 | 3,5,5,5,?,40,?,?,?,?,12,'average',?,'half','yes','half','good' 161 | 3,6,6,4,?,35,?,?,14,?,9,'generous','yes','full','yes','full','good' 162 | % 163 | % 164 | % 165 | -------------------------------------------------------------------------------- /content/zoo/zoo.csv: -------------------------------------------------------------------------------- 1 | animal,hair,feathers,eggs,milk,airborne,aquatic,predator,toothed,backbone,breathes,venomous,fins,legs,tail,domestic,catsize,type 2 | aardvark,true,false,false,true,false,false,true,true,true,true,false,false,4,false,false,true,mammal 3 | antelope,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 4 | bass,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 5 | bear,true,false,false,true,false,false,true,true,true,true,false,false,4,false,false,true,mammal 6 | boar,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 7 | buffalo,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 8 | calf,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 9 | carp,false,false,true,false,false,true,false,true,true,false,false,true,0,true,true,false,fish 10 | catfish,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 11 | cavy,true,false,false,true,false,false,false,true,true,true,false,false,4,false,true,false,mammal 12 | cheetah,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 13 | chicken,false,true,true,false,true,false,false,false,true,true,false,false,2,true,true,false,bird 14 | chub,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 15 | clam,false,false,true,false,false,false,true,false,false,false,false,false,0,false,false,false,invertebrate 16 | crab,false,false,true,false,false,true,true,false,false,false,false,false,4,false,false,false,invertebrate 17 | crayfish,false,false,true,false,false,true,true,false,false,false,false,false,6,false,false,false,invertebrate 18 | crow,false,true,true,false,true,false,true,false,true,true,false,false,2,true,false,false,bird 19 | deer,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 20 | dogfish,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,true,fish 21 | dolphin,false,false,false,true,false,true,true,true,true,true,false,true,0,true,false,true,mammal 22 | dove,false,true,true,false,true,false,false,false,true,true,false,false,2,true,true,false,bird 23 | duck,false,true,true,false,true,true,false,false,true,true,false,false,2,true,false,false,bird 24 | elephant,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 25 | flamingo,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,true,bird 26 | flea,false,false,true,false,false,false,false,false,false,true,false,false,6,false,false,false,insect 27 | frog,false,false,true,false,false,true,true,true,true,true,false,false,4,false,false,false,amphibian 28 | frog,false,false,true,false,false,true,true,true,true,true,true,false,4,false,false,false,amphibian 29 | fruitbat,true,false,false,true,true,false,false,true,true,true,false,false,2,true,false,false,mammal 30 | giraffe,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 31 | girl,true,false,false,true,false,false,true,true,true,true,false,false,2,false,true,true,mammal 32 | gnat,false,false,true,false,true,false,false,false,false,true,false,false,6,false,false,false,insect 33 | goat,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 34 | gorilla,true,false,false,true,false,false,false,true,true,true,false,false,2,false,false,true,mammal 35 | gull,false,true,true,false,true,true,true,false,true,true,false,false,2,true,false,false,bird 36 | haddock,false,false,true,false,false,true,false,true,true,false,false,true,0,true,false,false,fish 37 | hamster,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,false,mammal 38 | hare,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,false,mammal 39 | hawk,false,true,true,false,true,false,true,false,true,true,false,false,2,true,false,false,bird 40 | herring,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 41 | honeybee,true,false,true,false,true,false,false,false,false,true,true,false,6,false,true,false,insect 42 | housefly,true,false,true,false,true,false,false,false,false,true,false,false,6,false,false,false,insect 43 | kiwi,false,true,true,false,false,false,true,false,true,true,false,false,2,true,false,false,bird 44 | ladybird,false,false,true,false,true,false,true,false,false,true,false,false,6,false,false,false,insect 45 | lark,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 46 | leopard,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 47 | lion,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 48 | lobster,false,false,true,false,false,true,true,false,false,false,false,false,6,false,false,false,invertebrate 49 | lynx,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 50 | mink,true,false,false,true,false,true,true,true,true,true,false,false,4,true,false,true,mammal 51 | mole,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,false,mammal 52 | mongoose,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 53 | moth,true,false,true,false,true,false,false,false,false,true,false,false,6,false,false,false,insect 54 | newt,false,false,true,false,false,true,true,true,true,true,false,false,4,true,false,false,amphibian 55 | octopus,false,false,true,false,false,true,true,false,false,false,false,false,8,false,false,true,invertebrate 56 | opossum,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,false,mammal 57 | oryx,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 58 | ostrich,false,true,true,false,false,false,false,false,true,true,false,false,2,true,false,true,bird 59 | parakeet,false,true,true,false,true,false,false,false,true,true,false,false,2,true,true,false,bird 60 | penguin,false,true,true,false,false,true,true,false,true,true,false,false,2,true,false,true,bird 61 | pheasant,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 62 | pike,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,true,fish 63 | piranha,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 64 | pitviper,false,false,true,false,false,false,true,true,true,true,true,false,0,true,false,false,reptile 65 | platypus,true,false,true,true,false,true,true,false,true,true,false,false,4,true,false,true,mammal 66 | polecat,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 67 | pony,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 68 | porpoise,false,false,false,true,false,true,true,true,true,true,false,true,0,true,false,true,mammal 69 | puma,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 70 | pussycat,true,false,false,true,false,false,true,true,true,true,false,false,4,true,true,true,mammal 71 | raccoon,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 72 | reindeer,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 73 | rhea,false,true,true,false,false,false,true,false,true,true,false,false,2,true,false,true,bird 74 | scorpion,false,false,false,false,false,false,true,false,false,true,true,false,8,true,false,false,invertebrate 75 | seahorse,false,false,true,false,false,true,false,true,true,false,false,true,0,true,false,false,fish 76 | seal,true,false,false,true,false,true,true,true,true,true,false,true,0,false,false,true,mammal 77 | sealion,true,false,false,true,false,true,true,true,true,true,false,true,2,true,false,true,mammal 78 | seasnake,false,false,false,false,false,true,true,true,true,false,true,false,0,true,false,false,reptile 79 | seawasp,false,false,true,false,false,true,true,false,false,false,true,false,0,false,false,false,invertebrate 80 | skimmer,false,true,true,false,true,true,true,false,true,true,false,false,2,true,false,false,bird 81 | skua,false,true,true,false,true,true,true,false,true,true,false,false,2,true,false,false,bird 82 | slowworm,false,false,true,false,false,false,true,true,true,true,false,false,0,true,false,false,reptile 83 | slug,false,false,true,false,false,false,false,false,false,true,false,false,0,false,false,false,invertebrate 84 | sole,false,false,true,false,false,true,false,true,true,false,false,true,0,true,false,false,fish 85 | sparrow,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 86 | squirrel,true,false,false,true,false,false,false,true,true,true,false,false,2,true,false,false,mammal 87 | starfish,false,false,true,false,false,true,true,false,false,false,false,false,5,false,false,false,invertebrate 88 | stingray,false,false,true,false,false,true,true,true,true,false,true,true,0,true,false,true,fish 89 | swan,false,true,true,false,true,true,false,false,true,true,false,false,2,true,false,true,bird 90 | termite,false,false,true,false,false,false,false,false,false,true,false,false,6,false,false,false,insect 91 | toad,false,false,true,false,false,true,false,true,true,true,false,false,4,false,false,false,amphibian 92 | tortoise,false,false,true,false,false,false,false,false,true,true,false,false,4,true,false,true,reptile 93 | tuatara,false,false,true,false,false,false,true,true,true,true,false,false,4,true,false,false,reptile 94 | tuna,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,true,fish 95 | vampire,true,false,false,true,true,false,false,true,true,true,false,false,2,true,false,false,mammal 96 | vole,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,false,mammal 97 | vulture,false,true,true,false,true,false,true,false,true,true,false,false,2,true,false,true,bird 98 | wallaby,true,false,false,true,false,false,false,true,true,true,false,false,2,true,false,true,mammal 99 | wasp,true,false,true,false,true,false,false,false,false,true,true,false,6,false,false,false,insect 100 | wolf,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 101 | worm,false,false,true,false,false,false,false,false,false,true,false,false,0,false,false,false,invertebrate 102 | wren,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 103 | -------------------------------------------------------------------------------- /content/glass/glass.csv: -------------------------------------------------------------------------------- 1 | RI,Na,Mg,Al,Si,K,Ca,Ba,Fe,Type 2 | 1.51793,12.79,3.5,1.12,73.03,0.64,8.77,0,0,'build wind float' 3 | 1.51643,12.16,3.52,1.35,72.89,0.57,8.53,0,0,'vehic wind float' 4 | 1.51793,13.21,3.48,1.41,72.64,0.59,8.43,0,0,'build wind float' 5 | 1.51299,14.4,1.74,1.54,74.55,0,7.59,0,0,tableware 6 | 1.53393,12.3,0,1,70.16,0.12,16.19,0,0.24,'build wind non-float' 7 | 1.51655,12.75,2.85,1.44,73.27,0.57,8.79,0.11,0.22,'build wind non-float' 8 | 1.51779,13.64,3.65,0.65,73,0.06,8.93,0,0,'vehic wind float' 9 | 1.51837,13.14,2.84,1.28,72.85,0.55,9.07,0,0,'build wind float' 10 | 1.51545,14.14,0,2.68,73.39,0.08,9.07,0.61,0.05,headlamps 11 | 1.51789,13.19,3.9,1.3,72.33,0.55,8.44,0,0.28,'build wind non-float' 12 | 1.51625,13.36,3.58,1.49,72.72,0.45,8.21,0,0,'build wind non-float' 13 | 1.51743,12.2,3.25,1.16,73.55,0.62,8.9,0,0.24,'build wind non-float' 14 | 1.52223,13.21,3.77,0.79,71.99,0.13,10.02,0,0,'build wind float' 15 | 1.52121,14.03,3.76,0.58,71.79,0.11,9.65,0,0,'vehic wind float' 16 | 1.51665,13.14,3.45,1.76,72.48,0.6,8.38,0,0.17,'vehic wind float' 17 | 1.51707,13.48,3.48,1.71,72.52,0.62,7.99,0,0,'build wind non-float' 18 | 1.51719,14.75,0,2,73.02,0,8.53,1.59,0.08,headlamps 19 | 1.51629,12.71,3.33,1.49,73.28,0.67,8.24,0,0,'build wind non-float' 20 | 1.51994,13.27,0,1.76,73.03,0.47,11.32,0,0,containers 21 | 1.51811,12.96,2.96,1.43,72.92,0.6,8.79,0.14,0,'build wind non-float' 22 | 1.52152,13.05,3.65,0.87,72.22,0.19,9.85,0,0.17,'build wind float' 23 | 1.52475,11.45,0,1.88,72.19,0.81,13.24,0,0.34,'build wind non-float' 24 | 1.51841,12.93,3.74,1.11,72.28,0.64,8.96,0,0.22,'build wind non-float' 25 | 1.51754,13.39,3.66,1.19,72.79,0.57,8.27,0,0.11,'build wind float' 26 | 1.52058,12.85,1.61,2.17,72.18,0.76,9.7,0.24,0.51,containers 27 | 1.51569,13.24,3.49,1.47,73.25,0.38,8.03,0,0,'build wind non-float' 28 | 1.5159,12.82,3.52,1.9,72.86,0.69,7.97,0,0,'build wind non-float' 29 | 1.51683,14.56,0,1.98,73.29,0,8.52,1.57,0.07,headlamps 30 | 1.51687,13.23,3.54,1.48,72.84,0.56,8.1,0,0,'build wind non-float' 31 | 1.5161,13.33,3.53,1.34,72.67,0.56,8.33,0,0,'vehic wind float' 32 | 1.51674,12.87,3.56,1.64,73.14,0.65,7.99,0,0,'build wind non-float' 33 | 1.51832,13.33,3.34,1.54,72.14,0.56,8.99,0,0,'vehic wind float' 34 | 1.51115,17.38,0,0.34,75.41,0,6.65,0,0,tableware 35 | 1.51645,13.44,3.61,1.54,72.39,0.66,8.03,0,0,'build wind non-float' 36 | 1.51755,13,3.6,1.36,72.99,0.57,8.4,0,0.11,'build wind float' 37 | 1.51571,12.72,3.46,1.56,73.2,0.67,8.09,0,0.24,'build wind float' 38 | 1.51596,12.79,3.61,1.62,72.97,0.64,8.07,0,0.26,'build wind float' 39 | 1.5173,12.35,2.72,1.63,72.87,0.7,9.23,0,0,'build wind non-float' 40 | 1.51662,12.85,3.51,1.44,73.01,0.68,8.23,0.06,0.25,'build wind non-float' 41 | 1.51409,14.25,3.09,2.08,72.28,1.1,7.08,0,0,'build wind non-float' 42 | 1.51797,12.74,3.48,1.35,72.96,0.64,8.68,0,0,'build wind float' 43 | 1.51806,13,3.8,1.08,73.07,0.56,8.38,0,0.12,'build wind non-float' 44 | 1.51627,13,3.58,1.54,72.83,0.61,8.04,0,0,'build wind non-float' 45 | 1.5159,13.24,3.34,1.47,73.1,0.39,8.22,0,0,'build wind non-float' 46 | 1.51934,13.64,3.54,0.75,72.65,0.16,8.89,0.15,0.24,'vehic wind float' 47 | 1.51755,12.71,3.42,1.2,73.2,0.59,8.64,0,0,'build wind float' 48 | 1.51514,14.01,2.68,3.5,69.89,1.68,5.87,2.2,0,containers 49 | 1.51766,13.21,3.69,1.29,72.61,0.57,8.22,0,0,'build wind float' 50 | 1.51784,13.08,3.49,1.28,72.86,0.6,8.49,0,0,'build wind float' 51 | 1.52177,13.2,3.68,1.15,72.75,0.54,8.52,0,0,'build wind non-float' 52 | 1.51753,12.57,3.47,1.38,73.39,0.6,8.55,0,0.06,'build wind float' 53 | 1.51851,13.2,3.63,1.07,72.83,0.57,8.41,0.09,0.17,'build wind non-float' 54 | 1.51743,13.3,3.6,1.14,73.09,0.58,8.17,0,0,'build wind float' 55 | 1.51593,13.09,3.59,1.52,73.1,0.67,7.83,0,0,'build wind non-float' 56 | 1.5164,14.37,0,2.74,72.85,0,9.45,0.54,0,headlamps 57 | 1.51735,13.02,3.54,1.69,72.73,0.54,8.44,0,0.07,'build wind float' 58 | 1.52247,14.86,2.2,2.06,70.26,0.76,9.76,0,0,headlamps 59 | 1.52099,13.69,3.59,1.12,71.96,0.09,9.4,0,0,'build wind float' 60 | 1.51769,13.65,3.66,1.11,72.77,0.11,8.6,0,0,'vehic wind float' 61 | 1.51846,13.41,3.89,1.33,72.38,0.51,8.28,0,0,'build wind non-float' 62 | 1.51848,13.64,3.87,1.27,71.96,0.54,8.32,0,0.32,'build wind non-float' 63 | 1.51905,13.6,3.62,1.11,72.64,0.14,8.76,0,0,'build wind float' 64 | 1.51567,13.29,3.45,1.21,72.74,0.56,8.57,0,0,'build wind float' 65 | 1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float' 66 | 1.5232,13.72,3.72,0.51,71.75,0.09,10.06,0,0.16,'build wind float' 67 | 1.51556,13.87,0,2.54,73.23,0.14,9.41,0.81,0.01,headlamps 68 | 1.51926,13.2,3.33,1.28,72.36,0.6,9.14,0,0.11,'build wind float' 69 | 1.52211,14.19,3.78,0.91,71.36,0.23,9.14,0,0.37,'vehic wind float' 70 | 1.53125,10.73,0,2.1,69.81,0.58,13.3,3.15,0.28,'build wind non-float' 71 | 1.52152,13.05,3.65,0.87,72.32,0.19,9.85,0,0.17,'build wind float' 72 | 1.51829,14.46,2.24,1.62,72.38,0,9.26,0,0,tableware 73 | 1.51892,13.46,3.83,1.26,72.55,0.57,8.21,0,0.14,'build wind non-float' 74 | 1.51888,14.99,0.78,1.74,72.5,0,9.95,0,0,tableware 75 | 1.51829,13.24,3.9,1.41,72.33,0.55,8.31,0,0.1,'build wind non-float' 76 | 1.523,13.31,3.58,0.82,71.99,0.12,10.17,0,0.03,'build wind float' 77 | 1.51652,13.56,3.57,1.47,72.45,0.64,7.96,0,0,'build wind non-float' 78 | 1.51768,12.56,3.52,1.43,73.15,0.57,8.54,0,0,'build wind float' 79 | 1.51215,12.99,3.47,1.12,72.98,0.62,8.35,0,0.31,'build wind float' 80 | 1.51646,13.04,3.4,1.26,73.01,0.52,8.58,0,0,'vehic wind float' 81 | 1.51721,12.87,3.48,1.33,73.04,0.56,8.43,0,0,'build wind float' 82 | 1.51763,12.8,3.66,1.27,73.01,0.6,8.56,0,0,'build wind float' 83 | 1.51742,13.27,3.62,1.24,73.08,0.55,8.07,0,0,'build wind float' 84 | 1.52127,14.32,3.9,0.83,71.5,0,9.49,0,0,'vehic wind float' 85 | 1.51779,13.21,3.39,1.33,72.76,0.59,8.59,0,0,'build wind float' 86 | 1.52171,11.56,1.88,1.56,72.86,0.47,11.41,0,0,containers 87 | 1.518,13.71,3.93,1.54,71.81,0.54,8.21,0,0.15,'build wind non-float' 88 | 1.52777,12.64,0,0.67,72.02,0.06,14.4,0,0,'build wind non-float' 89 | 1.5175,12.82,3.55,1.49,72.75,0.54,8.52,0,0.19,'build wind float' 90 | 1.51764,12.98,3.54,1.21,73,0.65,8.53,0,0,'build wind float' 91 | 1.52177,13.75,1.01,1.36,72.19,0.33,11.14,0,0,'build wind non-float' 92 | 1.51645,14.94,0,1.87,73.11,0,8.67,1.38,0,headlamps 93 | 1.51786,12.73,3.43,1.19,72.95,0.62,8.76,0,0.3,'build wind float' 94 | 1.52152,13.12,3.58,0.9,72.2,0.23,9.82,0,0.16,'build wind float' 95 | 1.51937,13.79,2.41,1.19,72.76,0,9.77,0,0,tableware 96 | 1.51514,14.85,0,2.42,73.72,0,8.39,0.56,0,headlamps 97 | 1.52172,13.48,3.74,0.9,72.01,0.18,9.61,0,0.07,'build wind float' 98 | 1.51732,14.95,0,1.8,72.99,0,8.61,1.55,0,headlamps 99 | 1.5202,13.98,1.35,1.63,71.76,0.39,10.56,0,0.18,'build wind non-float' 100 | 1.51605,12.9,3.44,1.45,73.06,0.44,8.27,0,0,'build wind non-float' 101 | 1.51847,13.1,3.97,1.19,72.44,0.6,8.43,0,0,'build wind non-float' 102 | 1.51761,13.89,3.6,1.36,72.73,0.48,7.83,0,0,'build wind float' 103 | 1.51673,13.3,3.64,1.53,72.53,0.65,8.03,0,0.29,'build wind non-float' 104 | 1.52365,15.79,1.83,1.31,70.43,0.31,8.61,1.68,0,headlamps 105 | 1.51685,14.92,0,1.99,73.06,0,8.4,1.59,0,headlamps 106 | 1.51658,14.8,0,1.99,73.11,0,8.28,1.71,0,headlamps 107 | 1.51316,13.02,0,3.04,70.48,6.21,6.96,0,0,containers 108 | 1.51709,13,3.47,1.79,72.72,0.66,8.18,0,0,'build wind non-float' 109 | 1.51727,14.7,0,2.34,73.28,0,8.95,0.66,0,headlamps 110 | 1.51898,13.58,3.35,1.23,72.08,0.59,8.91,0,0,'build wind float' 111 | 1.51969,12.64,0,1.65,73.75,0.38,11.53,0,0,containers 112 | 1.5182,12.62,2.76,0.83,73.81,0.35,9.42,0,0.2,'build wind non-float' 113 | 1.51617,14.95,0,2.27,73.3,0,8.71,0.67,0,headlamps 114 | 1.51911,13.9,3.73,1.18,72.12,0.06,8.89,0,0,'build wind float' 115 | 1.51651,14.38,0,1.94,73.61,0,8.48,1.57,0,headlamps 116 | 1.51694,12.86,3.58,1.31,72.61,0.61,8.79,0,0,'vehic wind float' 117 | 1.52315,13.44,3.34,1.23,72.38,0.6,8.83,0,0,headlamps 118 | 1.52068,13.55,2.09,1.67,72.18,0.53,9.57,0.27,0.17,'build wind non-float' 119 | 1.51838,14.32,3.26,2.22,71.25,1.46,5.79,1.63,0,headlamps 120 | 1.51818,13.72,0,0.56,74.45,0,10.99,0,0,'build wind non-float' 121 | 1.51769,12.45,2.71,1.29,73.7,0.56,9.06,0,0.24,'build wind float' 122 | 1.5166,12.99,3.18,1.23,72.97,0.58,8.81,0,0.24,'build wind non-float' 123 | 1.51589,12.88,3.43,1.4,73.28,0.69,8.05,0,0.24,'build wind float' 124 | 1.5241,13.83,2.9,1.17,71.15,0.08,10.79,0,0,'build wind non-float' 125 | 1.52725,13.8,3.15,0.66,70.57,0.08,11.64,0,0,'build wind non-float' 126 | 1.52119,12.97,0.33,1.51,73.39,0.13,11.27,0,0.28,containers 127 | 1.51748,12.86,3.56,1.27,73.21,0.54,8.38,0,0.17,'build wind float' 128 | 1.51653,11.95,0,1.19,75.18,2.7,8.93,0,0,headlamps 129 | 1.51623,14.14,0,2.88,72.61,0.08,9.18,1.06,0,headlamps 130 | 1.52101,13.64,4.49,1.1,71.78,0.06,8.75,0,0,'build wind float' 131 | 1.51763,12.61,3.59,1.31,73.29,0.58,8.5,0,0,'build wind float' 132 | 1.51596,13.02,3.56,1.54,73.11,0.72,7.9,0,0,'build wind non-float' 133 | 1.51674,12.79,3.52,1.54,73.36,0.66,7.9,0,0,'build wind non-float' 134 | 1.52065,14.36,0,2.02,73.42,0,8.44,1.64,0,headlamps 135 | 1.51768,12.65,3.56,1.3,73.08,0.61,8.69,0,0.14,'build wind float' 136 | 1.52369,13.44,0,1.58,72.22,0.32,12.24,0,0,containers 137 | 1.51756,13.15,3.61,1.05,73.24,0.57,8.24,0,0,'build wind float' 138 | 1.51754,13.48,3.74,1.17,72.99,0.59,8.03,0,0,'build wind float' 139 | 1.51711,12.89,3.62,1.57,72.96,0.61,8.11,0,0,'build wind non-float' 140 | 1.5221,13.73,3.84,0.72,71.76,0.17,9.74,0,0,'build wind float' 141 | 1.51594,13.09,3.52,1.55,72.87,0.68,8.05,0,0.09,'build wind non-float' 142 | 1.51784,12.68,3.67,1.16,73.11,0.61,8.7,0,0,'build wind float' 143 | 1.51909,13.89,3.53,1.32,71.81,0.51,8.78,0.11,0,'build wind float' 144 | 1.51977,13.81,3.58,1.32,71.72,0.12,8.67,0.69,0,'build wind float' 145 | 1.51666,12.86,0,1.83,73.88,0.97,10.17,0,0,containers 146 | 1.51631,13.34,3.57,1.57,72.87,0.61,7.89,0,0,'build wind non-float' 147 | 1.51872,12.93,3.66,1.56,72.51,0.58,8.55,0,0.12,'build wind non-float' 148 | 1.51708,13.72,3.68,1.81,72.06,0.64,7.88,0,0,'build wind non-float' 149 | 1.52081,13.78,2.28,1.43,71.99,0.49,9.85,0,0.17,'build wind non-float' 150 | 1.51574,14.86,3.67,1.74,71.87,0.16,7.36,0,0.12,'build wind non-float' 151 | 1.51813,13.43,3.98,1.18,72.49,0.58,8.15,0,0,'build wind non-float' 152 | 1.51131,13.69,3.2,1.81,72.81,1.76,5.43,1.19,0,headlamps 153 | 1.52227,14.17,3.81,0.78,71.35,0,9.69,0,0,'build wind float' 154 | 1.52614,13.7,0,1.36,71.24,0.19,13.44,0,0.1,'build wind non-float' 155 | 1.51811,13.33,3.85,1.25,72.78,0.52,8.12,0,0,'build wind non-float' 156 | 1.51655,13.41,3.39,1.28,72.64,0.52,8.65,0,0,'vehic wind float' 157 | 1.51751,12.81,3.57,1.35,73.02,0.62,8.59,0,0,'build wind float' 158 | 1.51508,15.15,0,2.25,73.5,0,8.34,0.63,0,headlamps 159 | 1.51915,12.73,1.85,1.86,72.69,0.6,10.09,0,0,containers 160 | 1.51966,14.77,3.75,0.29,72.02,0.03,9,0,0,'build wind float' 161 | 1.51844,13.25,3.76,1.32,72.4,0.58,8.42,0,0,'build wind non-float' 162 | 1.52664,11.23,0,0.77,73.21,0,14.68,0,0,'build wind non-float' 163 | 1.52172,13.51,3.86,0.88,71.79,0.23,9.54,0,0.11,'build wind float' 164 | 1.51602,14.85,0,2.38,73.28,0,8.76,0.64,0.09,headlamps 165 | 1.51321,13,0,3.02,70.7,6.21,6.93,0,0,containers 166 | 1.52739,11.02,0,0.75,73.08,0,14.96,0,0,'build wind non-float' 167 | 1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float' 168 | 1.51747,12.84,3.5,1.14,73.27,0.56,8.55,0,0,'build wind float' 169 | 1.51839,12.85,3.67,1.24,72.57,0.62,8.68,0,0.35,'build wind non-float' 170 | 1.51646,13.41,3.55,1.25,72.81,0.68,8.1,0,0,'build wind non-float' 171 | 1.51609,15.01,0,2.51,73.05,0.05,8.83,0.53,0,headlamps 172 | 1.51667,12.94,3.61,1.26,72.75,0.56,8.6,0,0,'build wind non-float' 173 | 1.51588,13.12,3.41,1.58,73.26,0.07,8.39,0,0.19,'build wind non-float' 174 | 1.52667,13.99,3.7,0.71,71.57,0.02,9.82,0,0.1,'build wind float' 175 | 1.51831,14.39,0,1.82,72.86,1.41,6.47,2.88,0,headlamps 176 | 1.51918,14.04,3.58,1.37,72.08,0.56,8.3,0,0,'build wind float' 177 | 1.51613,13.88,1.78,1.79,73.1,0,8.67,0.76,0,headlamps 178 | 1.52196,14.36,3.85,0.89,71.36,0.15,9.15,0,0,'build wind float' 179 | 1.51824,12.87,3.48,1.29,72.95,0.6,8.43,0,0,'build wind float' 180 | 1.52151,11.03,1.71,1.56,73.44,0.58,11.62,0,0,containers 181 | 1.51969,14.56,0,0.56,73.48,0,11.22,0,0,tableware 182 | 1.51618,13.01,3.5,1.48,72.89,0.6,8.12,0,0,'build wind non-float' 183 | 1.51645,13.4,3.49,1.52,72.65,0.67,8.08,0,0.1,'build wind non-float' 184 | 1.51796,13.5,3.36,1.63,71.94,0.57,8.81,0,0.09,'vehic wind float' 185 | 1.52222,14.43,0,1,72.67,0.1,11.52,0,0.08,'build wind non-float' 186 | 1.51783,12.69,3.54,1.34,72.95,0.57,8.75,0,0,'build wind float' 187 | 1.51711,14.23,0,2.08,73.36,0,8.62,1.67,0,headlamps 188 | 1.51736,12.78,3.62,1.29,72.79,0.59,8.7,0,0,'build wind float' 189 | 1.51808,13.43,2.87,1.19,72.84,0.55,9.03,0,0,'build wind float' 190 | 1.5167,13.24,3.57,1.38,72.7,0.56,8.44,0,0.1,'vehic wind float' 191 | 1.52043,13.38,0,1.4,72.25,0.33,12.5,0,0,containers 192 | 1.519,13.49,3.48,1.35,71.95,0.55,9,0,0,'build wind float' 193 | 1.51778,13.21,2.81,1.29,72.98,0.51,9.02,0,0.09,'build wind float' 194 | 1.51905,14,2.39,1.56,72.37,0,9.57,0,0,tableware 195 | 1.51531,14.38,0,2.66,73.1,0.04,9.08,0.64,0,headlamps 196 | 1.51916,14.15,0,2.09,72.74,0,10.88,0,0,tableware 197 | 1.51841,13.02,3.62,1.06,72.34,0.64,9.13,0,0.15,'build wind non-float' 198 | 1.5159,13.02,3.58,1.51,73.12,0.69,7.96,0,0,'build wind non-float' 199 | 1.51593,13.25,3.45,1.43,73.17,0.61,7.86,0,0,'build wind non-float' 200 | 1.5164,12.55,3.48,1.87,73.23,0.63,8.08,0,0.09,'build wind non-float' 201 | 1.51663,12.93,3.54,1.62,72.96,0.64,8.03,0,0.21,'build wind non-float' 202 | 1.5169,13.33,3.54,1.61,72.54,0.68,8.11,0,0,'build wind non-float' 203 | 1.51869,13.19,3.37,1.18,72.72,0.57,8.83,0,0.16,'build wind float' 204 | 1.51776,13.53,3.41,1.52,72.04,0.58,8.79,0,0,'vehic wind float' 205 | 1.51775,12.85,3.48,1.23,72.97,0.61,8.56,0.09,0.22,'build wind float' 206 | 1.5186,13.36,3.43,1.43,72.26,0.51,8.6,0,0,'build wind non-float' 207 | 1.5172,13.38,3.5,1.15,72.85,0.5,8.43,0,0,'build wind float' 208 | 1.51623,14.2,0,2.79,73.46,0.04,9.04,0.4,0.09,headlamps 209 | 1.51618,13.53,3.55,1.54,72.99,0.39,7.78,0,0,'build wind float' 210 | 1.51761,12.81,3.54,1.23,73.24,0.58,8.39,0,0,'build wind float' 211 | 1.5161,13.42,3.4,1.22,72.69,0.59,8.32,0,0,'vehic wind float' 212 | 1.51592,12.86,3.52,2.12,72.66,0.69,7.97,0,0,'build wind non-float' 213 | 1.51613,13.92,3.52,1.25,72.88,0.37,7.94,0,0.14,'build wind non-float' 214 | 1.51689,12.67,2.88,1.71,73.21,0.73,8.54,0,0,'build wind non-float' 215 | 1.51852,14.09,2.19,1.66,72.67,0,9.32,0,0,tableware 216 | -------------------------------------------------------------------------------- /content/zoo/zoo.arff: -------------------------------------------------------------------------------- 1 | % Changes to WEKA Format: SRG - November 1994 2 | % 1. Boolean attributes changed from 1 and 0 to Enumerated attribute with 3 | % values {true and false} 4 | % 2. Class Number (Attribute 18) changed to an Enumerated type with 5 | % values {1,2,3,4,5,6,7} 6 | % 7 | % December 1997 - Changed class attribute values to semi-sensible names 8 | % 9 | % 1. Title: Zoo database 10 | % 11 | % 2. Source Information 12 | % -- Creator: Richard Forsyth 13 | % -- Donor: Richard S. Forsyth 14 | % 8 Grosvenor Avenue 15 | % Mapperley Park 16 | % Nottingham NG3 5DX 17 | % 0602-621676 18 | % -- Date: 5/15/1990 19 | % 20 | % 3. Past Usage: 21 | % -- None known other than what is shown in Forsyth's PC/BEAGLE User's Guide. 22 | % 23 | % 4. Relevant Information: 24 | % -- A simple database containing 17 Boolean-valued attributes. The "type" 25 | % attribute appears to be the class attribute. Here is a breakdown of 26 | % which animals are in which type: (I find it unusual that there are 27 | % 2 instances of "frog" and one of "girl"!) 28 | % 29 | % Class# Set of animals: 30 | % ====== =============================================================== 31 | % 1 (41) aardvark, antelope, bear, boar, buffalo, calf, 32 | % cavy, cheetah, deer, dolphin, elephant, 33 | % fruitbat, giraffe, girl, goat, gorilla, hamster, 34 | % hare, leopard, lion, lynx, mink, mole, mongoose, 35 | % opossum, oryx, platypus, polecat, pony, 36 | % porpoise, puma, pussycat, raccoon, reindeer, 37 | % seal, sealion, squirrel, vampire, vole, wallaby,wolf 38 | % 2 (20) chicken, crow, dove, duck, flamingo, gull, hawk, 39 | % kiwi, lark, ostrich, parakeet, penguin, pheasant, 40 | % rhea, skimmer, skua, sparrow, swan, vulture, wren 41 | % 3 (5) pitviper, seasnake, slowworm, tortoise, tuatara 42 | % 4 (13) bass, carp, catfish, chub, dogfish, haddock, 43 | % herring, pike, piranha, seahorse, sole, stingray, tuna 44 | % 5 (4) frog, frog, newt, toad 45 | % 6 (8) flea, gnat, honeybee, housefly, ladybird, moth, termite, wasp 46 | % 7 (10) clam, crab, crayfish, lobster, octopus, 47 | % scorpion, seawasp, slug, starfish, worm 48 | % 49 | % 5. Number of Instances: 101 50 | % 6. Number of Attributes: 18 (animal name, 15 Boolean attributes, 2 numerics) 51 | % 7. Attribute Information: (name of attribute and type of value domain) 52 | % 1. animal name: Unique for each instance 53 | % 2. hair Boolean 54 | % 3. feathers Boolean 55 | % 4. eggs Boolean 56 | % 5. milk Boolean 57 | % 6. airborne Boolean 58 | % 7. aquatic Boolean 59 | % 8. predator Boolean 60 | % 9. toothed Boolean 61 | % 10. backbone Boolean 62 | % 11. breathes Boolean 63 | % 12. venomous Boolean 64 | % 13. fins Boolean 65 | % 14. legs Numeric (set of values: {0,2,4,5,6,8}) 66 | % 15. tail Boolean 67 | % 16. domestic Boolean 68 | % 17. catsize Boolean 69 | % 18. type Numeric (integer values in range [1,7]) 70 | % 71 | % 8. Missing Attribute Values: None 72 | % 9. Class Distribution: Given above 73 | 74 | @RELATION zoo 75 | 76 | @ATTRIBUTE animal {aardvark,antelope,bass,bear,boar,buffalo,calf,carp,catfish,cavy,cheetah,chicken,chub,clam,crab,crayfish,crow,deer,dogfish,dolphin,dove,duck,elephant,flamingo,flea,frog,fruitbat,giraffe,girl,gnat,goat,gorilla,gull,haddock,hamster,hare,hawk,herring,honeybee,housefly,kiwi,ladybird,lark,leopard,lion,lobster,lynx,mink,mole,mongoose,moth,newt,octopus,opossum,oryx,ostrich,parakeet,penguin,pheasant,pike,piranha,pitviper,platypus,polecat,pony,porpoise,puma,pussycat,raccoon,reindeer,rhea,scorpion,seahorse,seal,sealion,seasnake,seawasp,skimmer,skua,slowworm,slug,sole,sparrow,squirrel,starfish,stingray,swan,termite,toad,tortoise,tuatara,tuna,vampire,vole,vulture,wallaby,wasp,wolf,worm,wren} 77 | @ATTRIBUTE hair {false, true} 78 | @ATTRIBUTE feathers {false, true} 79 | @ATTRIBUTE eggs {false, true} 80 | @ATTRIBUTE milk {false, true} 81 | @ATTRIBUTE airborne {false, true} 82 | @ATTRIBUTE aquatic {false, true} 83 | @ATTRIBUTE predator {false, true} 84 | @ATTRIBUTE toothed {false, true} 85 | @ATTRIBUTE backbone {false, true} 86 | @ATTRIBUTE breathes {false, true} 87 | @ATTRIBUTE venomous {false, true} 88 | @ATTRIBUTE fins {false, true} 89 | @ATTRIBUTE legs INTEGER [0,9] 90 | @ATTRIBUTE tail {false, true} 91 | @ATTRIBUTE domestic {false, true} 92 | @ATTRIBUTE catsize {false, true} 93 | @ATTRIBUTE type { mammal, bird, reptile, fish, amphibian, insect, invertebrate } 94 | 95 | @DATA 96 | % 97 | % Instances (101): 98 | % 99 | aardvark,true,false,false,true,false,false,true,true,true,true,false,false,4,false,false,true,mammal 100 | antelope,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 101 | bass,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 102 | bear,true,false,false,true,false,false,true,true,true,true,false,false,4,false,false,true,mammal 103 | boar,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 104 | buffalo,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 105 | calf,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 106 | carp,false,false,true,false,false,true,false,true,true,false,false,true,0,true,true,false,fish 107 | catfish,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 108 | cavy,true,false,false,true,false,false,false,true,true,true,false,false,4,false,true,false,mammal 109 | cheetah,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 110 | chicken,false,true,true,false,true,false,false,false,true,true,false,false,2,true,true,false,bird 111 | chub,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 112 | clam,false,false,true,false,false,false,true,false,false,false,false,false,0,false,false,false,invertebrate 113 | crab,false,false,true,false,false,true,true,false,false,false,false,false,4,false,false,false,invertebrate 114 | crayfish,false,false,true,false,false,true,true,false,false,false,false,false,6,false,false,false,invertebrate 115 | crow,false,true,true,false,true,false,true,false,true,true,false,false,2,true,false,false,bird 116 | deer,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 117 | dogfish,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,true,fish 118 | dolphin,false,false,false,true,false,true,true,true,true,true,false,true,0,true,false,true,mammal 119 | dove,false,true,true,false,true,false,false,false,true,true,false,false,2,true,true,false,bird 120 | duck,false,true,true,false,true,true,false,false,true,true,false,false,2,true,false,false,bird 121 | elephant,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 122 | flamingo,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,true,bird 123 | flea,false,false,true,false,false,false,false,false,false,true,false,false,6,false,false,false,insect 124 | frog,false,false,true,false,false,true,true,true,true,true,false,false,4,false,false,false,amphibian 125 | frog,false,false,true,false,false,true,true,true,true,true,true,false,4,false,false,false,amphibian 126 | fruitbat,true,false,false,true,true,false,false,true,true,true,false,false,2,true,false,false,mammal 127 | giraffe,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 128 | girl,true,false,false,true,false,false,true,true,true,true,false,false,2,false,true,true,mammal 129 | gnat,false,false,true,false,true,false,false,false,false,true,false,false,6,false,false,false,insect 130 | goat,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 131 | gorilla,true,false,false,true,false,false,false,true,true,true,false,false,2,false,false,true,mammal 132 | gull,false,true,true,false,true,true,true,false,true,true,false,false,2,true,false,false,bird 133 | haddock,false,false,true,false,false,true,false,true,true,false,false,true,0,true,false,false,fish 134 | hamster,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,false,mammal 135 | hare,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,false,mammal 136 | hawk,false,true,true,false,true,false,true,false,true,true,false,false,2,true,false,false,bird 137 | herring,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 138 | honeybee,true,false,true,false,true,false,false,false,false,true,true,false,6,false,true,false,insect 139 | housefly,true,false,true,false,true,false,false,false,false,true,false,false,6,false,false,false,insect 140 | kiwi,false,true,true,false,false,false,true,false,true,true,false,false,2,true,false,false,bird 141 | ladybird,false,false,true,false,true,false,true,false,false,true,false,false,6,false,false,false,insect 142 | lark,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 143 | leopard,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 144 | lion,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 145 | lobster,false,false,true,false,false,true,true,false,false,false,false,false,6,false,false,false,invertebrate 146 | lynx,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 147 | mink,true,false,false,true,false,true,true,true,true,true,false,false,4,true,false,true,mammal 148 | mole,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,false,mammal 149 | mongoose,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 150 | moth,true,false,true,false,true,false,false,false,false,true,false,false,6,false,false,false,insect 151 | newt,false,false,true,false,false,true,true,true,true,true,false,false,4,true,false,false,amphibian 152 | octopus,false,false,true,false,false,true,true,false,false,false,false,false,8,false,false,true,invertebrate 153 | opossum,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,false,mammal 154 | oryx,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,true,mammal 155 | ostrich,false,true,true,false,false,false,false,false,true,true,false,false,2,true,false,true,bird 156 | parakeet,false,true,true,false,true,false,false,false,true,true,false,false,2,true,true,false,bird 157 | penguin,false,true,true,false,false,true,true,false,true,true,false,false,2,true,false,true,bird 158 | pheasant,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 159 | pike,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,true,fish 160 | piranha,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,false,fish 161 | pitviper,false,false,true,false,false,false,true,true,true,true,true,false,0,true,false,false,reptile 162 | platypus,true,false,true,true,false,true,true,false,true,true,false,false,4,true,false,true,mammal 163 | polecat,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 164 | pony,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 165 | porpoise,false,false,false,true,false,true,true,true,true,true,false,true,0,true,false,true,mammal 166 | puma,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 167 | pussycat,true,false,false,true,false,false,true,true,true,true,false,false,4,true,true,true,mammal 168 | raccoon,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 169 | reindeer,true,false,false,true,false,false,false,true,true,true,false,false,4,true,true,true,mammal 170 | rhea,false,true,true,false,false,false,true,false,true,true,false,false,2,true,false,true,bird 171 | scorpion,false,false,false,false,false,false,true,false,false,true,true,false,8,true,false,false,invertebrate 172 | seahorse,false,false,true,false,false,true,false,true,true,false,false,true,0,true,false,false,fish 173 | seal,true,false,false,true,false,true,true,true,true,true,false,true,0,false,false,true,mammal 174 | sealion,true,false,false,true,false,true,true,true,true,true,false,true,2,true,false,true,mammal 175 | seasnake,false,false,false,false,false,true,true,true,true,false,true,false,0,true,false,false,reptile 176 | seawasp,false,false,true,false,false,true,true,false,false,false,true,false,0,false,false,false,invertebrate 177 | skimmer,false,true,true,false,true,true,true,false,true,true,false,false,2,true,false,false,bird 178 | skua,false,true,true,false,true,true,true,false,true,true,false,false,2,true,false,false,bird 179 | slowworm,false,false,true,false,false,false,true,true,true,true,false,false,0,true,false,false,reptile 180 | slug,false,false,true,false,false,false,false,false,false,true,false,false,0,false,false,false,invertebrate 181 | sole,false,false,true,false,false,true,false,true,true,false,false,true,0,true,false,false,fish 182 | sparrow,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 183 | squirrel,true,false,false,true,false,false,false,true,true,true,false,false,2,true,false,false,mammal 184 | starfish,false,false,true,false,false,true,true,false,false,false,false,false,5,false,false,false,invertebrate 185 | stingray,false,false,true,false,false,true,true,true,true,false,true,true,0,true,false,true,fish 186 | swan,false,true,true,false,true,true,false,false,true,true,false,false,2,true,false,true,bird 187 | termite,false,false,true,false,false,false,false,false,false,true,false,false,6,false,false,false,insect 188 | toad,false,false,true,false,false,true,false,true,true,true,false,false,4,false,false,false,amphibian 189 | tortoise,false,false,true,false,false,false,false,false,true,true,false,false,4,true,false,true,reptile 190 | tuatara,false,false,true,false,false,false,true,true,true,true,false,false,4,true,false,false,reptile 191 | tuna,false,false,true,false,false,true,true,true,true,false,false,true,0,true,false,true,fish 192 | vampire,true,false,false,true,true,false,false,true,true,true,false,false,2,true,false,false,mammal 193 | vole,true,false,false,true,false,false,false,true,true,true,false,false,4,true,false,false,mammal 194 | vulture,false,true,true,false,true,false,true,false,true,true,false,false,2,true,false,true,bird 195 | wallaby,true,false,false,true,false,false,false,true,true,true,false,false,2,true,false,true,mammal 196 | wasp,true,false,true,false,true,false,false,false,false,true,true,false,6,false,false,false,insect 197 | wolf,true,false,false,true,false,false,true,true,true,true,false,false,4,true,false,true,mammal 198 | worm,false,false,true,false,false,false,false,false,false,true,false,false,0,false,false,false,invertebrate 199 | wren,false,true,true,false,true,false,false,false,true,true,false,false,2,true,false,false,bird 200 | % 201 | % 202 | % 203 | -------------------------------------------------------------------------------- /content/glass/glass.arff: -------------------------------------------------------------------------------- 1 | % 1. Title: Glass Identification Database 2 | % 3 | % 2. Sources: 4 | % (a) Creator: B. German 5 | % -- Central Research Establishment 6 | % Home Office Forensic Science Service 7 | % Aldermaston, Reading, Berkshire RG7 4PN 8 | % (b) Donor: Vina Spiehler, Ph.D., DABFT 9 | % Diagnostic Products Corporation 10 | % (213) 776-0180 (ext 3014) 11 | % (c) Date: September, 1987 12 | % 13 | % 3. Past Usage: 14 | % -- Rule Induction in Forensic Science 15 | % -- Ian W. Evett and Ernest J. Spiehler 16 | % -- Central Research Establishment 17 | % Home Office Forensic Science Service 18 | % Aldermaston, Reading, Berkshire RG7 4PN 19 | % -- Unknown technical note number (sorry, not listed here) 20 | % -- General Results: nearest neighbor held its own with respect to the 21 | % rule-based system 22 | % 23 | % 4. Relevant Information:n 24 | % Vina conducted a comparison test of her rule-based system, BEAGLE, the 25 | % nearest-neighbor algorithm, and discriminant analysis. BEAGLE is 26 | % a product available through VRS Consulting, Inc.; 4676 Admiralty Way, 27 | % Suite 206; Marina Del Ray, CA 90292 (213) 827-7890 and FAX: -3189. 28 | % In determining whether the glass was a type of "float" glass or not, 29 | % the following results were obtained (# incorrect answers): 30 | % 31 | % Type of Sample Beagle NN DA 32 | % Windows that were float processed (87) 10 12 21 33 | % Windows that were not: (76) 19 16 22 34 | % 35 | % The study of classification of types of glass was motivated by 36 | % criminological investigation. At the scene of the crime, the glass left 37 | % can be used as evidence...if it is correctly identified! 38 | % 39 | % 5. Number of Instances: 214 40 | % 41 | % 6. Number of Attributes: 10 (including an Id#) plus the class attribute 42 | % -- all attributes are continuously valued 43 | % 44 | % 7. Attribute Information: 45 | % 1. Id number: 1 to 214 46 | % 2. RI: refractive index 47 | % 3. Na: Sodium (unit measurement: weight percent in corresponding oxide, as 48 | % are attributes 4-10) 49 | % 4. Mg: Magnesium 50 | % 5. Al: Aluminum 51 | % 6. Si: Silicon 52 | % 7. K: Potassium 53 | % 8. Ca: Calcium 54 | % 9. Ba: Barium 55 | % 10. Fe: Iron 56 | % 11. Type of glass: (class attribute) 57 | % -- 1 building_windows_float_processed 58 | % -- 2 building_windows_non_float_processed 59 | % -- 3 vehicle_windows_float_processed 60 | % -- 4 vehicle_windows_non_float_processed (none in this database) 61 | % -- 5 containers 62 | % -- 6 tableware 63 | % -- 7 headlamps 64 | % 65 | % 8. Missing Attribute Values: None 66 | % 67 | % Summary Statistics: 68 | % Attribute: Min Max Mean SD Correlation with class 69 | % 2. RI: 1.5112 1.5339 1.5184 0.0030 -0.1642 70 | % 3. Na: 10.73 17.38 13.4079 0.8166 0.5030 71 | % 4. Mg: 0 4.49 2.6845 1.4424 -0.7447 72 | % 5. Al: 0.29 3.5 1.4449 0.4993 0.5988 73 | % 6. Si: 69.81 75.41 72.6509 0.7745 0.1515 74 | % 7. K: 0 6.21 0.4971 0.6522 -0.0100 75 | % 8. Ca: 5.43 16.19 8.9570 1.4232 0.0007 76 | % 9. Ba: 0 3.15 0.1750 0.4972 0.5751 77 | % 10. Fe: 0 0.51 0.0570 0.0974 -0.1879 78 | % 79 | % 9. Class Distribution: (out of 214 total instances) 80 | % -- 163 Window glass (building windows and vehicle windows) 81 | % -- 87 float processed 82 | % -- 70 building windows 83 | % -- 17 vehicle windows 84 | % -- 76 non-float processed 85 | % -- 76 building windows 86 | % -- 0 vehicle windows 87 | % -- 51 Non-window glass 88 | % -- 13 containers 89 | % -- 9 tableware 90 | % -- 29 headlamps 91 | % 92 | % 93 | % 94 | % 95 | % 96 | % 97 | % 98 | % Relabeled values in attribute 'Type' 99 | % From: '1' To: 'build wind float' 100 | % From: '2' To: 'build wind non-float' 101 | % From: '3' To: 'vehic wind float' 102 | % From: '4' To: 'vehic wind non-float' 103 | % From: '5' To: containers 104 | % From: '6' To: tableware 105 | % From: '7' To: headlamps 106 | % 107 | @relation Glass 108 | @attribute 'RI' real 109 | @attribute 'Na' real 110 | @attribute 'Mg' real 111 | @attribute 'Al' real 112 | @attribute 'Si' real 113 | @attribute 'K' real 114 | @attribute 'Ca' real 115 | @attribute 'Ba' real 116 | @attribute 'Fe' real 117 | @attribute 'Type' { 'build wind float', 'build wind non-float', 'vehic wind float', 'vehic wind non-float', containers, tableware, headlamps} 118 | @data 119 | 1.51793,12.79,3.5,1.12,73.03,0.64,8.77,0,0,'build wind float' 120 | 1.51643,12.16,3.52,1.35,72.89,0.57,8.53,0,0,'vehic wind float' 121 | 1.51793,13.21,3.48,1.41,72.64,0.59,8.43,0,0,'build wind float' 122 | 1.51299,14.4,1.74,1.54,74.55,0,7.59,0,0,tableware 123 | 1.53393,12.3,0,1,70.16,0.12,16.19,0,0.24,'build wind non-float' 124 | 1.51655,12.75,2.85,1.44,73.27,0.57,8.79,0.11,0.22,'build wind non-float' 125 | 1.51779,13.64,3.65,0.65,73,0.06,8.93,0,0,'vehic wind float' 126 | 1.51837,13.14,2.84,1.28,72.85,0.55,9.07,0,0,'build wind float' 127 | 1.51545,14.14,0,2.68,73.39,0.08,9.07,0.61,0.05,headlamps 128 | 1.51789,13.19,3.9,1.3,72.33,0.55,8.44,0,0.28,'build wind non-float' 129 | 1.51625,13.36,3.58,1.49,72.72,0.45,8.21,0,0,'build wind non-float' 130 | 1.51743,12.2,3.25,1.16,73.55,0.62,8.9,0,0.24,'build wind non-float' 131 | 1.52223,13.21,3.77,0.79,71.99,0.13,10.02,0,0,'build wind float' 132 | 1.52121,14.03,3.76,0.58,71.79,0.11,9.65,0,0,'vehic wind float' 133 | 1.51665,13.14,3.45,1.76,72.48,0.6,8.38,0,0.17,'vehic wind float' 134 | 1.51707,13.48,3.48,1.71,72.52,0.62,7.99,0,0,'build wind non-float' 135 | 1.51719,14.75,0,2,73.02,0,8.53,1.59,0.08,headlamps 136 | 1.51629,12.71,3.33,1.49,73.28,0.67,8.24,0,0,'build wind non-float' 137 | 1.51994,13.27,0,1.76,73.03,0.47,11.32,0,0,containers 138 | 1.51811,12.96,2.96,1.43,72.92,0.6,8.79,0.14,0,'build wind non-float' 139 | 1.52152,13.05,3.65,0.87,72.22,0.19,9.85,0,0.17,'build wind float' 140 | 1.52475,11.45,0,1.88,72.19,0.81,13.24,0,0.34,'build wind non-float' 141 | 1.51841,12.93,3.74,1.11,72.28,0.64,8.96,0,0.22,'build wind non-float' 142 | 1.51754,13.39,3.66,1.19,72.79,0.57,8.27,0,0.11,'build wind float' 143 | 1.52058,12.85,1.61,2.17,72.18,0.76,9.7,0.24,0.51,containers 144 | 1.51569,13.24,3.49,1.47,73.25,0.38,8.03,0,0,'build wind non-float' 145 | 1.5159,12.82,3.52,1.9,72.86,0.69,7.97,0,0,'build wind non-float' 146 | 1.51683,14.56,0,1.98,73.29,0,8.52,1.57,0.07,headlamps 147 | 1.51687,13.23,3.54,1.48,72.84,0.56,8.1,0,0,'build wind non-float' 148 | 1.5161,13.33,3.53,1.34,72.67,0.56,8.33,0,0,'vehic wind float' 149 | 1.51674,12.87,3.56,1.64,73.14,0.65,7.99,0,0,'build wind non-float' 150 | 1.51832,13.33,3.34,1.54,72.14,0.56,8.99,0,0,'vehic wind float' 151 | 1.51115,17.38,0,0.34,75.41,0,6.65,0,0,tableware 152 | 1.51645,13.44,3.61,1.54,72.39,0.66,8.03,0,0,'build wind non-float' 153 | 1.51755,13,3.6,1.36,72.99,0.57,8.4,0,0.11,'build wind float' 154 | 1.51571,12.72,3.46,1.56,73.2,0.67,8.09,0,0.24,'build wind float' 155 | 1.51596,12.79,3.61,1.62,72.97,0.64,8.07,0,0.26,'build wind float' 156 | 1.5173,12.35,2.72,1.63,72.87,0.7,9.23,0,0,'build wind non-float' 157 | 1.51662,12.85,3.51,1.44,73.01,0.68,8.23,0.06,0.25,'build wind non-float' 158 | 1.51409,14.25,3.09,2.08,72.28,1.1,7.08,0,0,'build wind non-float' 159 | 1.51797,12.74,3.48,1.35,72.96,0.64,8.68,0,0,'build wind float' 160 | 1.51806,13,3.8,1.08,73.07,0.56,8.38,0,0.12,'build wind non-float' 161 | 1.51627,13,3.58,1.54,72.83,0.61,8.04,0,0,'build wind non-float' 162 | 1.5159,13.24,3.34,1.47,73.1,0.39,8.22,0,0,'build wind non-float' 163 | 1.51934,13.64,3.54,0.75,72.65,0.16,8.89,0.15,0.24,'vehic wind float' 164 | 1.51755,12.71,3.42,1.2,73.2,0.59,8.64,0,0,'build wind float' 165 | 1.51514,14.01,2.68,3.5,69.89,1.68,5.87,2.2,0,containers 166 | 1.51766,13.21,3.69,1.29,72.61,0.57,8.22,0,0,'build wind float' 167 | 1.51784,13.08,3.49,1.28,72.86,0.6,8.49,0,0,'build wind float' 168 | 1.52177,13.2,3.68,1.15,72.75,0.54,8.52,0,0,'build wind non-float' 169 | 1.51753,12.57,3.47,1.38,73.39,0.6,8.55,0,0.06,'build wind float' 170 | 1.51851,13.2,3.63,1.07,72.83,0.57,8.41,0.09,0.17,'build wind non-float' 171 | 1.51743,13.3,3.6,1.14,73.09,0.58,8.17,0,0,'build wind float' 172 | 1.51593,13.09,3.59,1.52,73.1,0.67,7.83,0,0,'build wind non-float' 173 | 1.5164,14.37,0,2.74,72.85,0,9.45,0.54,0,headlamps 174 | 1.51735,13.02,3.54,1.69,72.73,0.54,8.44,0,0.07,'build wind float' 175 | 1.52247,14.86,2.2,2.06,70.26,0.76,9.76,0,0,headlamps 176 | 1.52099,13.69,3.59,1.12,71.96,0.09,9.4,0,0,'build wind float' 177 | 1.51769,13.65,3.66,1.11,72.77,0.11,8.6,0,0,'vehic wind float' 178 | 1.51846,13.41,3.89,1.33,72.38,0.51,8.28,0,0,'build wind non-float' 179 | 1.51848,13.64,3.87,1.27,71.96,0.54,8.32,0,0.32,'build wind non-float' 180 | 1.51905,13.6,3.62,1.11,72.64,0.14,8.76,0,0,'build wind float' 181 | 1.51567,13.29,3.45,1.21,72.74,0.56,8.57,0,0,'build wind float' 182 | 1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float' 183 | 1.5232,13.72,3.72,0.51,71.75,0.09,10.06,0,0.16,'build wind float' 184 | 1.51556,13.87,0,2.54,73.23,0.14,9.41,0.81,0.01,headlamps 185 | 1.51926,13.2,3.33,1.28,72.36,0.6,9.14,0,0.11,'build wind float' 186 | 1.52211,14.19,3.78,0.91,71.36,0.23,9.14,0,0.37,'vehic wind float' 187 | 1.53125,10.73,0,2.1,69.81,0.58,13.3,3.15,0.28,'build wind non-float' 188 | 1.52152,13.05,3.65,0.87,72.32,0.19,9.85,0,0.17,'build wind float' 189 | 1.51829,14.46,2.24,1.62,72.38,0,9.26,0,0,tableware 190 | 1.51892,13.46,3.83,1.26,72.55,0.57,8.21,0,0.14,'build wind non-float' 191 | 1.51888,14.99,0.78,1.74,72.5,0,9.95,0,0,tableware 192 | 1.51829,13.24,3.9,1.41,72.33,0.55,8.31,0,0.1,'build wind non-float' 193 | 1.523,13.31,3.58,0.82,71.99,0.12,10.17,0,0.03,'build wind float' 194 | 1.51652,13.56,3.57,1.47,72.45,0.64,7.96,0,0,'build wind non-float' 195 | 1.51768,12.56,3.52,1.43,73.15,0.57,8.54,0,0,'build wind float' 196 | 1.51215,12.99,3.47,1.12,72.98,0.62,8.35,0,0.31,'build wind float' 197 | 1.51646,13.04,3.4,1.26,73.01,0.52,8.58,0,0,'vehic wind float' 198 | 1.51721,12.87,3.48,1.33,73.04,0.56,8.43,0,0,'build wind float' 199 | 1.51763,12.8,3.66,1.27,73.01,0.6,8.56,0,0,'build wind float' 200 | 1.51742,13.27,3.62,1.24,73.08,0.55,8.07,0,0,'build wind float' 201 | 1.52127,14.32,3.9,0.83,71.5,0,9.49,0,0,'vehic wind float' 202 | 1.51779,13.21,3.39,1.33,72.76,0.59,8.59,0,0,'build wind float' 203 | 1.52171,11.56,1.88,1.56,72.86,0.47,11.41,0,0,containers 204 | 1.518,13.71,3.93,1.54,71.81,0.54,8.21,0,0.15,'build wind non-float' 205 | 1.52777,12.64,0,0.67,72.02,0.06,14.4,0,0,'build wind non-float' 206 | 1.5175,12.82,3.55,1.49,72.75,0.54,8.52,0,0.19,'build wind float' 207 | 1.51764,12.98,3.54,1.21,73,0.65,8.53,0,0,'build wind float' 208 | 1.52177,13.75,1.01,1.36,72.19,0.33,11.14,0,0,'build wind non-float' 209 | 1.51645,14.94,0,1.87,73.11,0,8.67,1.38,0,headlamps 210 | 1.51786,12.73,3.43,1.19,72.95,0.62,8.76,0,0.3,'build wind float' 211 | 1.52152,13.12,3.58,0.9,72.2,0.23,9.82,0,0.16,'build wind float' 212 | 1.51937,13.79,2.41,1.19,72.76,0,9.77,0,0,tableware 213 | 1.51514,14.85,0,2.42,73.72,0,8.39,0.56,0,headlamps 214 | 1.52172,13.48,3.74,0.9,72.01,0.18,9.61,0,0.07,'build wind float' 215 | 1.51732,14.95,0,1.8,72.99,0,8.61,1.55,0,headlamps 216 | 1.5202,13.98,1.35,1.63,71.76,0.39,10.56,0,0.18,'build wind non-float' 217 | 1.51605,12.9,3.44,1.45,73.06,0.44,8.27,0,0,'build wind non-float' 218 | 1.51847,13.1,3.97,1.19,72.44,0.6,8.43,0,0,'build wind non-float' 219 | 1.51761,13.89,3.6,1.36,72.73,0.48,7.83,0,0,'build wind float' 220 | 1.51673,13.3,3.64,1.53,72.53,0.65,8.03,0,0.29,'build wind non-float' 221 | 1.52365,15.79,1.83,1.31,70.43,0.31,8.61,1.68,0,headlamps 222 | 1.51685,14.92,0,1.99,73.06,0,8.4,1.59,0,headlamps 223 | 1.51658,14.8,0,1.99,73.11,0,8.28,1.71,0,headlamps 224 | 1.51316,13.02,0,3.04,70.48,6.21,6.96,0,0,containers 225 | 1.51709,13,3.47,1.79,72.72,0.66,8.18,0,0,'build wind non-float' 226 | 1.51727,14.7,0,2.34,73.28,0,8.95,0.66,0,headlamps 227 | 1.51898,13.58,3.35,1.23,72.08,0.59,8.91,0,0,'build wind float' 228 | 1.51969,12.64,0,1.65,73.75,0.38,11.53,0,0,containers 229 | 1.5182,12.62,2.76,0.83,73.81,0.35,9.42,0,0.2,'build wind non-float' 230 | 1.51617,14.95,0,2.27,73.3,0,8.71,0.67,0,headlamps 231 | 1.51911,13.9,3.73,1.18,72.12,0.06,8.89,0,0,'build wind float' 232 | 1.51651,14.38,0,1.94,73.61,0,8.48,1.57,0,headlamps 233 | 1.51694,12.86,3.58,1.31,72.61,0.61,8.79,0,0,'vehic wind float' 234 | 1.52315,13.44,3.34,1.23,72.38,0.6,8.83,0,0,headlamps 235 | 1.52068,13.55,2.09,1.67,72.18,0.53,9.57,0.27,0.17,'build wind non-float' 236 | 1.51838,14.32,3.26,2.22,71.25,1.46,5.79,1.63,0,headlamps 237 | 1.51818,13.72,0,0.56,74.45,0,10.99,0,0,'build wind non-float' 238 | 1.51769,12.45,2.71,1.29,73.7,0.56,9.06,0,0.24,'build wind float' 239 | 1.5166,12.99,3.18,1.23,72.97,0.58,8.81,0,0.24,'build wind non-float' 240 | 1.51589,12.88,3.43,1.4,73.28,0.69,8.05,0,0.24,'build wind float' 241 | 1.5241,13.83,2.9,1.17,71.15,0.08,10.79,0,0,'build wind non-float' 242 | 1.52725,13.8,3.15,0.66,70.57,0.08,11.64,0,0,'build wind non-float' 243 | 1.52119,12.97,0.33,1.51,73.39,0.13,11.27,0,0.28,containers 244 | 1.51748,12.86,3.56,1.27,73.21,0.54,8.38,0,0.17,'build wind float' 245 | 1.51653,11.95,0,1.19,75.18,2.7,8.93,0,0,headlamps 246 | 1.51623,14.14,0,2.88,72.61,0.08,9.18,1.06,0,headlamps 247 | 1.52101,13.64,4.49,1.1,71.78,0.06,8.75,0,0,'build wind float' 248 | 1.51763,12.61,3.59,1.31,73.29,0.58,8.5,0,0,'build wind float' 249 | 1.51596,13.02,3.56,1.54,73.11,0.72,7.9,0,0,'build wind non-float' 250 | 1.51674,12.79,3.52,1.54,73.36,0.66,7.9,0,0,'build wind non-float' 251 | 1.52065,14.36,0,2.02,73.42,0,8.44,1.64,0,headlamps 252 | 1.51768,12.65,3.56,1.3,73.08,0.61,8.69,0,0.14,'build wind float' 253 | 1.52369,13.44,0,1.58,72.22,0.32,12.24,0,0,containers 254 | 1.51756,13.15,3.61,1.05,73.24,0.57,8.24,0,0,'build wind float' 255 | 1.51754,13.48,3.74,1.17,72.99,0.59,8.03,0,0,'build wind float' 256 | 1.51711,12.89,3.62,1.57,72.96,0.61,8.11,0,0,'build wind non-float' 257 | 1.5221,13.73,3.84,0.72,71.76,0.17,9.74,0,0,'build wind float' 258 | 1.51594,13.09,3.52,1.55,72.87,0.68,8.05,0,0.09,'build wind non-float' 259 | 1.51784,12.68,3.67,1.16,73.11,0.61,8.7,0,0,'build wind float' 260 | 1.51909,13.89,3.53,1.32,71.81,0.51,8.78,0.11,0,'build wind float' 261 | 1.51977,13.81,3.58,1.32,71.72,0.12,8.67,0.69,0,'build wind float' 262 | 1.51666,12.86,0,1.83,73.88,0.97,10.17,0,0,containers 263 | 1.51631,13.34,3.57,1.57,72.87,0.61,7.89,0,0,'build wind non-float' 264 | 1.51872,12.93,3.66,1.56,72.51,0.58,8.55,0,0.12,'build wind non-float' 265 | 1.51708,13.72,3.68,1.81,72.06,0.64,7.88,0,0,'build wind non-float' 266 | 1.52081,13.78,2.28,1.43,71.99,0.49,9.85,0,0.17,'build wind non-float' 267 | 1.51574,14.86,3.67,1.74,71.87,0.16,7.36,0,0.12,'build wind non-float' 268 | 1.51813,13.43,3.98,1.18,72.49,0.58,8.15,0,0,'build wind non-float' 269 | 1.51131,13.69,3.2,1.81,72.81,1.76,5.43,1.19,0,headlamps 270 | 1.52227,14.17,3.81,0.78,71.35,0,9.69,0,0,'build wind float' 271 | 1.52614,13.7,0,1.36,71.24,0.19,13.44,0,0.1,'build wind non-float' 272 | 1.51811,13.33,3.85,1.25,72.78,0.52,8.12,0,0,'build wind non-float' 273 | 1.51655,13.41,3.39,1.28,72.64,0.52,8.65,0,0,'vehic wind float' 274 | 1.51751,12.81,3.57,1.35,73.02,0.62,8.59,0,0,'build wind float' 275 | 1.51508,15.15,0,2.25,73.5,0,8.34,0.63,0,headlamps 276 | 1.51915,12.73,1.85,1.86,72.69,0.6,10.09,0,0,containers 277 | 1.51966,14.77,3.75,0.29,72.02,0.03,9,0,0,'build wind float' 278 | 1.51844,13.25,3.76,1.32,72.4,0.58,8.42,0,0,'build wind non-float' 279 | 1.52664,11.23,0,0.77,73.21,0,14.68,0,0,'build wind non-float' 280 | 1.52172,13.51,3.86,0.88,71.79,0.23,9.54,0,0.11,'build wind float' 281 | 1.51602,14.85,0,2.38,73.28,0,8.76,0.64,0.09,headlamps 282 | 1.51321,13,0,3.02,70.7,6.21,6.93,0,0,containers 283 | 1.52739,11.02,0,0.75,73.08,0,14.96,0,0,'build wind non-float' 284 | 1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float' 285 | 1.51747,12.84,3.5,1.14,73.27,0.56,8.55,0,0,'build wind float' 286 | 1.51839,12.85,3.67,1.24,72.57,0.62,8.68,0,0.35,'build wind non-float' 287 | 1.51646,13.41,3.55,1.25,72.81,0.68,8.1,0,0,'build wind non-float' 288 | 1.51609,15.01,0,2.51,73.05,0.05,8.83,0.53,0,headlamps 289 | 1.51667,12.94,3.61,1.26,72.75,0.56,8.6,0,0,'build wind non-float' 290 | 1.51588,13.12,3.41,1.58,73.26,0.07,8.39,0,0.19,'build wind non-float' 291 | 1.52667,13.99,3.7,0.71,71.57,0.02,9.82,0,0.1,'build wind float' 292 | 1.51831,14.39,0,1.82,72.86,1.41,6.47,2.88,0,headlamps 293 | 1.51918,14.04,3.58,1.37,72.08,0.56,8.3,0,0,'build wind float' 294 | 1.51613,13.88,1.78,1.79,73.1,0,8.67,0.76,0,headlamps 295 | 1.52196,14.36,3.85,0.89,71.36,0.15,9.15,0,0,'build wind float' 296 | 1.51824,12.87,3.48,1.29,72.95,0.6,8.43,0,0,'build wind float' 297 | 1.52151,11.03,1.71,1.56,73.44,0.58,11.62,0,0,containers 298 | 1.51969,14.56,0,0.56,73.48,0,11.22,0,0,tableware 299 | 1.51618,13.01,3.5,1.48,72.89,0.6,8.12,0,0,'build wind non-float' 300 | 1.51645,13.4,3.49,1.52,72.65,0.67,8.08,0,0.1,'build wind non-float' 301 | 1.51796,13.5,3.36,1.63,71.94,0.57,8.81,0,0.09,'vehic wind float' 302 | 1.52222,14.43,0,1,72.67,0.1,11.52,0,0.08,'build wind non-float' 303 | 1.51783,12.69,3.54,1.34,72.95,0.57,8.75,0,0,'build wind float' 304 | 1.51711,14.23,0,2.08,73.36,0,8.62,1.67,0,headlamps 305 | 1.51736,12.78,3.62,1.29,72.79,0.59,8.7,0,0,'build wind float' 306 | 1.51808,13.43,2.87,1.19,72.84,0.55,9.03,0,0,'build wind float' 307 | 1.5167,13.24,3.57,1.38,72.7,0.56,8.44,0,0.1,'vehic wind float' 308 | 1.52043,13.38,0,1.4,72.25,0.33,12.5,0,0,containers 309 | 1.519,13.49,3.48,1.35,71.95,0.55,9,0,0,'build wind float' 310 | 1.51778,13.21,2.81,1.29,72.98,0.51,9.02,0,0.09,'build wind float' 311 | 1.51905,14,2.39,1.56,72.37,0,9.57,0,0,tableware 312 | 1.51531,14.38,0,2.66,73.1,0.04,9.08,0.64,0,headlamps 313 | 1.51916,14.15,0,2.09,72.74,0,10.88,0,0,tableware 314 | 1.51841,13.02,3.62,1.06,72.34,0.64,9.13,0,0.15,'build wind non-float' 315 | 1.5159,13.02,3.58,1.51,73.12,0.69,7.96,0,0,'build wind non-float' 316 | 1.51593,13.25,3.45,1.43,73.17,0.61,7.86,0,0,'build wind non-float' 317 | 1.5164,12.55,3.48,1.87,73.23,0.63,8.08,0,0.09,'build wind non-float' 318 | 1.51663,12.93,3.54,1.62,72.96,0.64,8.03,0,0.21,'build wind non-float' 319 | 1.5169,13.33,3.54,1.61,72.54,0.68,8.11,0,0,'build wind non-float' 320 | 1.51869,13.19,3.37,1.18,72.72,0.57,8.83,0,0.16,'build wind float' 321 | 1.51776,13.53,3.41,1.52,72.04,0.58,8.79,0,0,'vehic wind float' 322 | 1.51775,12.85,3.48,1.23,72.97,0.61,8.56,0.09,0.22,'build wind float' 323 | 1.5186,13.36,3.43,1.43,72.26,0.51,8.6,0,0,'build wind non-float' 324 | 1.5172,13.38,3.5,1.15,72.85,0.5,8.43,0,0,'build wind float' 325 | 1.51623,14.2,0,2.79,73.46,0.04,9.04,0.4,0.09,headlamps 326 | 1.51618,13.53,3.55,1.54,72.99,0.39,7.78,0,0,'build wind float' 327 | 1.51761,12.81,3.54,1.23,73.24,0.58,8.39,0,0,'build wind float' 328 | 1.5161,13.42,3.4,1.22,72.69,0.59,8.32,0,0,'vehic wind float' 329 | 1.51592,12.86,3.52,2.12,72.66,0.69,7.97,0,0,'build wind non-float' 330 | 1.51613,13.92,3.52,1.25,72.88,0.37,7.94,0,0.14,'build wind non-float' 331 | 1.51689,12.67,2.88,1.71,73.21,0.73,8.54,0,0,'build wind non-float' 332 | 1.51852,14.09,2.19,1.66,72.67,0,9.32,0,0,tableware 333 | -------------------------------------------------------------------------------- /content/divorce/divorce.csv: -------------------------------------------------------------------------------- 1 | Atr1;Atr2;Atr3;Atr4;Atr5;Atr6;Atr7;Atr8;Atr9;Atr10;Atr11;Atr12;Atr13;Atr14;Atr15;Atr16;Atr17;Atr18;Atr19;Atr20;Atr21;Atr22;Atr23;Atr24;Atr25;Atr26;Atr27;Atr28;Atr29;Atr30;Atr31;Atr32;Atr33;Atr34;Atr35;Atr36;Atr37;Atr38;Atr39;Atr40;Atr41;Atr42;Atr43;Atr44;Atr45;Atr46;Atr47;Atr48;Atr49;Atr50;Atr51;Atr52;Atr53;Atr54;Class 2 | 2;2;4;1;0;0;0;0;0;0;1;0;1;1;0;1;0;0;0;1;0;0;0;0;0;0;0;0;0;1;1;2;1;2;0;1;2;1;3;3;2;1;1;2;3;2;1;3;3;3;2;3;2;1;1 3 | 4;4;4;4;4;0;0;4;4;4;4;3;4;0;4;4;4;4;3;2;1;1;0;2;2;1;2;0;1;1;0;4;2;3;0;2;3;4;2;4;2;2;3;4;2;2;2;3;4;4;4;4;2;2;1 4 | 2;2;2;2;1;3;2;1;1;2;3;4;2;3;3;3;3;3;3;2;1;0;1;2;2;2;2;2;3;2;3;3;1;1;1;1;2;1;3;3;3;3;2;3;2;3;2;3;1;1;1;2;2;2;1 5 | 3;2;3;2;3;3;3;3;3;3;4;3;3;4;3;3;3;3;3;4;1;1;1;1;2;1;1;1;1;3;2;3;2;2;1;1;3;3;4;4;2;2;3;2;3;2;2;3;3;3;3;2;2;2;1 6 | 2;2;1;1;1;1;0;0;0;0;0;1;0;1;1;1;1;1;2;1;1;0;0;0;0;2;1;2;1;1;1;1;1;1;0;0;0;0;2;1;0;2;3;0;2;2;1;2;3;2;2;2;1;0;1 7 | 0;0;1;0;0;2;0;0;0;1;0;2;1;0;2;0;2;1;0;1;0;0;0;0;2;2;0;0;0;0;4;1;1;1;1;1;1;2;0;2;2;1;2;3;0;2;2;1;2;1;1;1;2;0;1 8 | 3;3;3;2;1;3;4;3;2;2;2;2;2;3;2;3;3;3;3;2;3;3;3;3;2;3;3;2;2;2;1;2;2;1;1;2;3;2;2;3;3;3;3;4;3;3;2;3;2;3;3;2;2;2;1 9 | 2;1;2;2;2;1;0;3;3;2;4;3;2;3;4;3;2;3;2;1;2;1;1;2;3;3;2;2;2;3;1;1;0;2;2;1;4;4;4;4;4;4;3;2;0;0;1;2;2;2;1;1;1;0;1 10 | 2;2;1;0;0;4;1;3;3;3;3;3;3;3;3;3;3;3;3;3;2;2;2;3;2;3;2;3;2;3;1;1;1;1;1;1;1;2;2;2;2;2;2;2;2;1;1;1;1;1;1;1;1;1;1 11 | 1;1;1;1;1;2;0;2;2;2;3;0;0;2;1;0;1;2;1;0;0;0;0;1;1;1;1;1;1;1;1;1;0;1;0;0;1;1;2;2;1;2;3;2;2;2;0;2;2;2;2;4;3;3;1 12 | 4;4;4;3;4;0;0;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 13 | 4;4;4;3;4;0;0;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 14 | 3;4;3;4;3;0;1;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 15 | 3;4;3;4;3;0;1;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 16 | 3;4;3;4;3;0;1;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;4;1 17 | 4;4;3;2;4;0;0;4;3;2;4;4;4;4;3;2;4;4;4;4;3;2;4;4;4;4;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 18 | 4;4;3;2;4;0;0;4;3;2;4;4;4;4;3;2;4;4;4;4;3;2;4;4;4;4;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 19 | 4;4;4;3;4;0;0;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 20 | 3;3;4;4;3;1;1;3;4;4;3;3;3;3;4;4;3;3;3;3;4;4;3;3;3;3;4;4;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 21 | 4;4;4;3;4;0;0;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;4;4;3;4;4;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 22 | 4;3;3;3;4;1;0;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 23 | 4;3;3;3;4;1;0;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 24 | 3;4;4;4;3;0;1;4;4;4;3;4;3;4;4;4;3;4;3;4;4;4;3;4;3;4;4;4;3;4;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;3;4;3;4;4;3;4;3;4;1 25 | 3;3;3;4;3;1;1;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 26 | 4;2;3;4;4;2;0;2;3;4;4;2;4;2;3;4;4;2;4;2;3;4;4;2;4;2;3;4;4;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 27 | 3;3;3;4;3;1;1;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 28 | 3;3;4;3;3;1;1;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;1 29 | 3;3;3;4;3;1;1;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;1 30 | 3;4;3;2;3;0;1;4;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 31 | 4;3;3;2;4;1;0;3;3;2;4;3;4;3;3;2;4;3;4;3;3;2;4;3;4;3;3;2;4;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 32 | 3;4;3;2;3;0;1;4;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 33 | 4;3;4;3;4;1;0;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 34 | 4;3;3;4;4;1;0;3;3;4;4;3;4;3;3;4;4;3;4;3;3;4;4;3;4;3;3;4;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 35 | 3;4;2;3;3;0;1;4;2;3;3;4;3;4;2;3;3;4;3;4;2;3;3;4;3;4;2;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;1 36 | 3;4;4;3;3;0;1;4;4;3;3;4;3;4;4;3;3;4;3;4;4;3;3;4;3;4;4;3;3;4;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 37 | 3;3;3;3;3;1;1;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 38 | 4;3;3;3;4;1;0;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;4;3;4;3;4;4;3;4;4;4;4;3;4;4;3;4;4;3;3;4;4;3;1 39 | 3;3;2;3;3;1;1;3;3;3;4;3;3;3;3;3;3;3;4;3;3;3;3;4;3;3;2;4;3;4;4;4;4;4;4;4;4;4;4;4;4;3;4;3;3;3;4;4;4;4;3;3;4;4;1 40 | 3;3;2;3;3;1;1;3;3;3;4;3;3;3;3;3;3;3;4;3;3;3;3;4;3;3;2;4;3;4;4;4;4;4;4;4;4;4;4;4;4;3;4;3;3;3;4;4;4;4;3;3;4;4;1 41 | 4;3;3;3;4;1;0;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 42 | 3;2;3;4;3;2;1;2;3;4;3;2;3;2;3;4;3;2;3;2;3;4;3;2;3;2;3;4;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;1 43 | 4;2;3;2;4;2;0;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 44 | 3;4;3;3;3;0;1;4;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;4;3;4;3;1 45 | 3;3;3;2;3;1;1;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 46 | 4;2;3;2;4;2;0;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 47 | 3;3;2;3;3;1;1;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 48 | 3;3;3;2;3;1;1;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 49 | 3;3;2;3;3;1;1;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 50 | 4;2;3;2;4;2;0;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 51 | 3;3;3;2;3;1;1;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 52 | 4;2;3;2;4;2;0;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;2;3;2;4;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 53 | 3;3;3;2;3;1;1;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;4;4;4;4;4;4;4;4;4;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;1 54 | 4;3;2;3;4;1;0;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 55 | 3;3;3;4;3;1;1;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;3;3;3;4;3;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;4;3;4;3;1 56 | 4;3;3;2;4;1;0;3;3;2;4;3;4;3;3;2;4;3;4;3;3;2;4;3;4;3;3;2;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;3;4;3;4;4;3;4;3;4;1 57 | 4;3;2;3;4;1;0;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;3;4;3;2;3;4;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;4;3;4;3;1 58 | 3;4;3;4;3;0;1;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;1 59 | 3;4;3;4;3;0;1;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;1 60 | 3;3;3;3;3;1;1;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 61 | 3;2;3;2;3;2;1;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 62 | 3;2;3;2;3;2;1;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 63 | 3;2;2;3;3;2;1;2;2;3;3;2;3;2;2;3;3;2;3;2;2;3;3;2;3;2;2;3;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 64 | 3;2;3;2;3;2;1;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 65 | 3;2;3;2;3;2;1;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;1 66 | 3;3;4;4;3;1;1;3;4;4;3;3;3;3;4;4;3;3;3;3;4;4;3;3;3;3;4;4;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;1 67 | 3;3;3;2;3;1;1;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 68 | 3;3;2;3;3;1;1;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 69 | 4;2;2;3;4;2;0;2;2;3;4;2;4;2;2;3;4;2;4;2;2;3;4;2;4;2;2;3;4;2;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;4;3;4;3;4;1 70 | 3;3;3;2;3;1;1;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;3;4;3;4;4;3;4;3;4;1 71 | 4;4;4;3;4;2;4;4;4;3;4;4;4;4;4;4;4;4;4;4;4;3;0;4;0;4;4;0;4;4;0;4;4;0;1;0;2;0;4;0;2;4;4;1;4;0;4;4;4;3;4;4;4;4;1 72 | 3;3;3;2;3;1;1;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;3;3;2;3;3;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;4;3;3;4;3;4;3;1 73 | 2;2;3;2;2;2;2;2;3;2;2;2;2;2;3;2;2;2;2;2;3;2;2;2;2;2;3;2;2;2;4;4;4;4;4;4;4;4;4;4;4;3;4;4;4;4;4;4;4;4;4;4;4;4;1 74 | 3;3;3;3;3;1;1;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;3;1 75 | 4;3;3;3;3;1;4;0;4;3;3;3;3;4;3;3;3;3;3;3;3;3;2;2;2;2;3;2;2;2;2;4;3;3;3;3;3;4;4;4;3;3;3;3;3;3;3;3;3;3;3;3;3;3;1 76 | 3;2;3;2;3;2;1;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;2;3;4;3;4;3;4;3;4;3;4;3;3;3;4;3;4;3;4;3;3;4;3;4;3;1 77 | 4;4;3;3;4;0;4;2;4;4;3;4;4;4;4;4;4;4;4;4;0;0;2;4;4;4;4;1;1;0;4;2;0;0;0;0;3;0;4;4;4;4;4;4;4;2;4;4;3;4;4;1;1;0;1 78 | 3;2;4;3;3;2;3;2;2;3;4;3;2;3;1;3;3;3;3;4;2;1;0;2;2;2;2;2;2;3;3;3;3;3;3;3;4;4;4;4;4;3;0;0;0;0;0;3;3;3;3;3;3;3;1 79 | 2;2;2;3;2;3;2;1;3;2;1;2;2;2;3;3;3;3;3;2;2;1;1;3;3;3;2;3;2;2;3;3;3;3;3;3;3;3;4;4;4;4;3;4;2;2;3;3;2;1;1;2;2;2;1 80 | 3;2;4;3;3;2;3;2;2;3;4;3;2;2;1;3;3;3;3;4;2;1;0;2;2;2;2;2;2;3;3;3;3;3;3;3;4;4;4;4;3;0;0;3;0;0;0;3;3;3;3;3;3;3;1 81 | 4;2;4;2;1;2;3;1;1;3;3;3;2;2;3;2;2;3;3;2;2;2;2;3;4;4;3;3;3;4;4;4;2;2;0;0;4;3;4;4;3;1;1;4;1;2;1;3;3;3;3;1;1;1;1 82 | 2;0;2;4;2;2;4;3;4;3;2;3;3;0;4;4;3;3;3;2;2;1;2;0;0;0;0;0;2;2;3;3;3;3;3;3;3;3;1;3;2;3;3;4;4;2;3;2;2;3;3;4;2;2;1 83 | 4;4;3;3;2;0;2;4;4;3;4;3;4;3;4;4;4;3;3;3;2;3;3;3;3;3;1;3;3;2;3;3;3;4;4;4;4;4;4;4;4;2;2;3;2;2;2;2;2;3;3;3;3;4;1 84 | 4;4;3;4;4;0;0;4;4;4;4;4;4;4;4;3;3;4;4;3;2;2;3;1;2;2;1;3;2;2;3;3;1;2;1;4;4;3;3;3;1;3;3;3;3;1;2;3;2;2;2;2;1;2;1 85 | 3;3;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;0;0;0;2;0;0;0;0;0;2;3;3;3;4;4;4;4;4;4;4;4;1;1;1;1;1;1;3;2;2;2;4;4;4;1 86 | 0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;1;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;1;0;0;0;1;0;0;0;1;0;0;1;0 87 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;2;3;1;0;0;1;1;0;0;0;0 88 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;0;0;1;0;0;0;0;0;0;0;0;0;0;0;1;0;2;0;1;1;1;1;0;0;0;1;1;1;0 89 | 0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;3;0;0;0;0;2;0;0;1;2;2;1;0 90 | 4;0;3;4;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;4;0;0;0;0;0;0;0 91 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;2;1;0;1;1;0;1;0;0;0;0;0;0;0;0;1;1;1;1;1;0;1;1;0 92 | 0;1;0;0;0;0;0;1;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;1;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;3;1;0;3;0;1;0;0;0;2;0;0;0 93 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;0;0;0;0;0;0;0;0;0;0;2;0;0;2;0;2;3;2;2;1;1;0;0 94 | 1;1;0;0;0;0;0;0;0;1;0;0;1;0;0;0;0;0;0;0;1;0;0;0;1;0;1;1;1;1;0;0;0;0;0;0;0;0;0;0;0;1;2;0;2;1;0;0;1;1;1;1;1;1;0 95 | 0;1;0;1;0;0;0;0;0;1;0;0;0;1;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;1;1;1;0;0;0;2;1;0;0;0;2;1;1;1;1;2;1;1;1;0;0;0;0 96 | 0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;0;0;0;0;2;1;1;1;0;0;2;0;1;0;1;0;0;0;0;0;0;2;2;2;2;1;0;0;0 97 | 0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;3;2;0;2;2;2;2;2;2;2;0 98 | 0;3;1;0;0;0;0;0;0;0;0;1;1;2;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;0;1;0;0;0;0;0;0;1;0;1;0;1;1;1;4;0;0;2;0;0;0;0 99 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;4;2;0;0;0;0;0;0;0;0;1;4;2;0;4;2;1;1;0;0;0;1;0;0;0 100 | 0;0;0;0;0;2;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;2;1;4;2;3;0;0;0;2;4;1;0 101 | 0;1;2;1;0;0;0;0;0;0;0;1;1;0;0;0;1;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;2;2;0;1;0;1;2;0;0;0;3;2;1;0 102 | 0;0;2;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;1;0;1;0;0;1;0;0;0;0;0;2;0;2;2;1;2;0;0;0;4;4;0;0 103 | 0;0;1;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;1;0;2;0;1;0;0;0;0;0;0;0;0;3;0;0;2;2;0;0;1;1;3;4;0;0 104 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;2;4;2;3;1;1;2;0;0;1;4;1;2;0 105 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;1;1;1;1;0;0;0;0;0;0;0;0;0;2;0;3;0;3;3;1;2;1;1;1;0;1;0;0 106 | 0;0;0;0;0;1;0;0;0;0;1;1;1;0;0;0;0;0;1;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;3;0;3;4;3;0;2;2;2;0;0;0;0 107 | 0;0;0;0;0;0;0;0;0;0;0;1;1;1;1;0;0;0;0;0;1;1;0;0;0;0;0;1;0;0;0;0;0;1;0;0;1;0;1;0;0;0;2;2;2;0;0;2;2;2;2;1;1;0;0 108 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;4;0;4;3;1;3;1;3;3;3;1;0;0 109 | 0;0;0;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;4;0;0;0;0;0;0;0;0;3;0;2;2;2;2;4;4;0;0 110 | 0;0;3;0;0;1;0;0;0;0;0;2;0;0;1;0;1;0;0;1;0;0;0;0;1;0;0;0;0;1;0;2;0;0;0;0;0;0;1;0;0;0;1;0;1;1;1;3;3;2;2;0;0;0;0 111 | 0;0;0;0;0;1;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;0;0;1;0;0;1;0;0;0;1;1;2;0;1;2;2;2;2;2;2;2;2;2;0 112 | 0;0;0;0;0;0;0;0;0;0;0;0;1;1;0;0;0;0;0;0;1;0;0;0;1;0;0;1;1;1;1;0;0;0;0;0;0;0;0;0;0;1;3;2;1;3;0;2;3;3;2;1;0;0;0 113 | 1;1;1;1;1;0;0;1;1;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;0;0;0;0;0;0;0;0;2;2;3;3;3;3;1;1;0;0 114 | 0;0;0;0;1;0;0;0;0;0;0;0;1;0;1;0;0;0;0;0;0;0;0;0;1;1;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;2;3;1;3;3;3;2;1;1;1;1;1;1;0 115 | 0;2;2;1;0;0;0;0;0;2;1;1;1;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;1;3;0;0;0;0;2;1;0;2;0;0;0;0;0;0;0;3;1;1;1;0;3;0;0 116 | 0;1;1;0;0;0;0;0;0;1;1;1;2;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;1;2;0;0;0;0;1;0;1;0;3;1;4;0;2;2;0;1;0;0;1;0;0 117 | 0;1;1;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;1;2;0;1;4;4;3;3;1;2;3;1;1;0 118 | 0;0;0;0;0;2;0;0;0;0;0;0;1;0;0;1;1;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;1;0;0;1;0;0;0;0;2;4;0;4;3;1;1;2;2;2;1;0;0;0 119 | 0;0;0;0;0;1;0;1;1;0;0;0;1;1;0;0;0;0;0;0;1;1;1;0;1;0;0;0;0;1;1;1;1;1;0;0;1;0;0;0;0;0;0;0;0;0;0;2;1;2;2;3;3;2;0 120 | 0;0;0;0;0;1;0;0;0;1;0;1;1;0;0;1;0;0;0;0;0;0;0;0;2;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;0;4;1;1;4;4;2;2;0;1;0 121 | 0;1;1;0;0;2;0;0;0;0;0;2;1;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;1;0;2;0;0;0;0;0;0;0;0;0;2;2;2;2;2;2;2;0;2;1;1;1;0;0 122 | 0;0;0;0;0;2;0;0;0;1;0;0;0;0;1;0;1;0;1;0;0;0;0;0;0;0;0;0;0;1;0;1;0;1;0;0;1;1;1;0;0;4;2;0;1;2;1;3;1;1;1;1;1;0;0 123 | 0;2;2;1;0;0;0;0;0;2;1;1;1;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;1;3;0;0;0;0;2;1;1;0;2;0;0;0;0;0;0;3;1;1;1;0;3;0;0 124 | 0;0;1;0;1;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;1;2;0;0;0;2;0;1;0;0;0;2;0;1;2;1;3;3;2;2;2;2;0;0 125 | 0;0;0;0;0;2;0;0;0;0;0;0;1;1;0;0;0;0;0;0;0;0;0;0;1;1;1;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;2;1;0;3;0;2;3;4;3;3;0;2;0 126 | 0;1;1;0;0;0;0;0;0;0;0;1;3;0;0;0;0;0;0;0;0;0;0;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;2;4;0;2;4;0;3;0;1;2;2;2;0;0 127 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;1;1;0;1;1;2;1;2;2;4;2;4;0;0;0;1;1;2;1;0;2;0 128 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;1;1;0;1;1;2;1;2;2;4;2;4;0;0;0;1;1;2;1;0;2;0 129 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;0;0;0;1;1;0;0;3;2;1;3;3;0;2;3;2;2;4;1;1;0 130 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;4;4;4;3;0;0;4;1;1;0;1;0;0;0;0;0;0;0;0;0;4;2;2;2;0 131 | 0;0;0;0;0;0;0;0;0;1;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;2;0;0;0;0;0;0;0;0;0;4;4;0;4;1;4;2;3;2;2;0;0;0;0 132 | 0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;1;0;0;0;1;1;0;0;0;1;1;1;1;1;1;0;0;0;0;0;0;1;1;1;0;1;0;1;2;2;2;2;2;2;2;2;0;1;0;0 133 | 0;1;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;1;1;1;0;0;2;1;2;2;1;2;2;0;1;3;0;2;2;2;2;0;0;0;0 134 | 0;0;2;0;2;4;0;0;0;0;0;0;2;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;3;0;1;0;0;1;0;0;0;1;0;4;0;1;1;2;3;0;1;1;0;0;0;0 135 | 1;2;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;1;0;0;1;1;1;1;1;0;0;0;0;2;1;0;1;0;0;1;0;0;0;1;0;2;0;0;2;1;2;2;2;2;2;1;0;0 136 | 1;0;1;0;0;0;0;1;0;0;1;0;1;0;0;1;0;0;1;0;0;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;0;1;0;0;0;0;2;0;2;0;2;3;0;3;3;3;2;2;0 137 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;1;1;1;0;0;0;1;1;0;0;3;2;1;2;2;1;2;3;2;2;3;1;1;0 138 | 0;0;2;0;0;0;0;0;0;0;0;1;1;0;0;0;1;0;0;0;0;0;0;0;1;0;0;0;0;0;2;1;0;2;3;0;1;0;2;0;0;0;0;0;2;3;1;2;1;2;1;2;2;0;0 139 | 0;0;1;0;0;0;0;1;1;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;1;0;0;0;0;0;0;0;2;2;0;3;3;3;3;0;1;3;3;3;1;0 140 | 0;0;1;0;0;0;0;1;1;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;1;0;0;0;0;0;0;0;2;2;0;3;3;3;3;0;1;3;3;3;1;0 141 | 3;1;1;0;0;0;0;0;0;0;1;0;0;1;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;3;0;0;1;1;1;0;3;3;2;2;0;2;2;0;0;4;0 142 | 0;2;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;0;0;0;2;0;0;0;1;0;0;1;1;2;0;1;2;3;0;1;1;2;2;1;0;1;3;2;2;0 143 | 0;1;2;0;0;0;0;0;0;1;1;1;2;1;1;1;0;0;1;0;1;0;0;0;0;0;0;0;0;0;1;1;0;1;0;0;1;1;1;1;1;1;1;0;1;1;0;2;1;1;1;1;1;1;0 144 | 4;3;4;4;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;4;4;4;4;0;0;0;0 145 | 3;0;0;0;0;0;0;0;0;0;0;1;1;2;1;0;0;1;1;0;0;0;0;1;0;0;1;0;0;0;0;0;0;0;0;0;0;0;1;1;0;0;3;2;4;4;0;1;0;0;1;4;1;0;0 146 | 0;0;2;4;0;0;0;0;0;2;0;0;0;0;0;0;0;0;2;0;0;0;0;0;0;0;0;0;0;0;0;2;0;1;0;0;0;2;0;0;2;2;3;0;3;2;0;2;4;0;0;1;0;0;0 147 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;1;1;0;1;3;4;0;4;3;4;3;1;3;3;0;1;0;0 148 | 2;1;1;0;0;1;0;0;0;0;0;1;0;1;0;0;1;0;1;0;0;0;0;1;0;1;1;0;0;0;0;1;0;2;0;0;1;0;2;1;2;1;3;1;3;1;1;3;0;0;0;0;0;0;0 149 | 0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;2;2;1;1;1;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;4;4;4;4;4;0;4;0;0;0;0;0;0 150 | 0;0;0;0;0;0;0;0;0;2;0;1;1;0;0;0;0;0;0;0;1;0;0;1;1;0;0;0;1;0;2;0;0;1;0;0;1;0;2;0;1;3;2;0;1;3;3;2;2;1;1;2;0;0;0 151 | 0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;4;4;4;4;4;4;4;2;2;0;0;0;0 152 | 0;3;2;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;1;0;0;4;4;0;4;4;4;3;1;1;1;2;0;1;0 153 | 0;1;1;1;1;0;0;0;0;0;1;1;2;1;1;1;1;1;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;0;0;1;1;0;1;3;1;2;1;2;2;2;2;1;0 154 | 1;0;0;0;0;1;0;0;0;1;1;0;1;1;1;1;0;1;0;0;0;0;0;1;1;0;0;0;0;1;1;0;0;0;0;0;0;0;0;0;0;2;4;1;0;2;1;2;1;2;2;4;2;0;0 155 | 2;2;3;0;0;1;0;0;0;1;1;1;1;1;1;1;1;1;1;1;1;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;0;0;0;0;0;0;2;0;2;2;1;1;1;1;1;1;1;1;0 156 | 1;0;1;0;1;1;0;0;0;1;0;0;1;1;1;0;0;1;0;1;0;0;0;0;0;0;0;0;0;0;1;1;1;1;0;0;1;0;1;1;1;1;1;1;1;0;0;2;1;2;2;2;2;3;0 157 | 2;1;0;2;0;0;0;0;0;1;1;1;1;0;1;0;1;1;0;0;0;0;0;1;1;1;0;0;0;0;0;0;1;0;1;0;1;0;1;0;0;0;1;0;0;3;0;2;2;2;2;2;2;1;0 158 | 0;0;1;1;0;0;0;0;0;2;1;2;1;1;1;0;0;0;0;0;0;0;0;0;1;0;0;0;0;1;2;1;0;2;0;0;1;1;1;1;0;2;2;0;0;2;1;2;1;2;2;1;0;0;0 159 | 0;1;0;0;0;1;0;2;0;0;1;0;1;0;0;0;0;0;0;0;0;0;2;2;0;0;1;1;0;0;1;0;0;0;0;0;0;0;0;0;3;1;1;0;1;3;3;2;0;0;0;4;4;2;0 160 | 0;1;0;1;0;0;0;0;0;1;1;2;2;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;0;0;2;1;0;0;0;0;1;1;2;1;0;2;2;2;1;0;1;3;2;2;2;1;0;0;0 161 | 0;0;0;0;0;0;0;0;0;1;0;1;2;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;1;1;1;0;0;1;1;2;1;1;3;2;0;2;1;2;3;2;2;2;1;1;0;0 162 | 2;0;2;0;0;0;0;0;0;2;0;0;2;0;0;1;1;0;0;0;1;1;0;0;0;0;0;0;0;0;1;1;0;1;1;1;1;0;1;1;0;2;1;0;0;3;2;2;1;1;1;1;2;1;0 163 | 1;1;2;0;2;1;0;2;1;2;1;1;2;0;2;1;2;1;0;0;0;1;0;1;1;0;1;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;1;1;1;0;1;2;2;0;1;1;0 164 | 0;0;0;0;0;2;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;2;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;2;2;4;4;4;2;2;2;2;4;2;2;0 165 | 2;0;1;0;0;0;0;0;0;2;1;0;1;0;2;2;1;0;0;0;1;0;0;1;0;1;0;0;0;0;2;0;0;0;0;0;2;2;1;0;0;2;2;1;2;3;0;2;0;0;2;1;0;0;0 166 | 2;1;1;0;0;2;0;0;0;2;0;1;1;1;1;0;0;0;0;0;0;0;0;0;1;1;0;0;0;1;1;1;2;2;0;0;0;0;0;0;1;0;1;2;0;1;0;3;1;1;3;1;1;1;0 167 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;4;4;3;4;0;0;4;0;1;0;1;0;0;0;0;1;0;4;1;1;4;2;2;2;0 168 | 0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;1;1;1;1;1;1;1;1;1;1;3;1;3;4;1;2;2;2;2;3;2;2;0 169 | 1;1;0;0;0;0;0;0;0;1;0;1;1;0;0;1;0;0;0;1;0;0;0;0;1;1;1;0;0;1;1;1;0;1;0;0;1;1;1;2;1;3;3;0;2;3;0;2;0;1;1;3;0;0;0 170 | 0;0;0;0;0;0;0;0;0;0;0;1;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;1;0;0;1;0;4;1;2;1;1;0;4;3;3;2;2;3;2;4;3;1;0 171 | 0;0;0;0;0;0;0;1;0;0;0;1;1;1;0;0;0;0;0;1;1;0;1;1;0;0;0;0;0;0;1;3;0;0;0;0;0;0;0;0;0;2;2;0;1;3;4;4;0;1;3;3;3;1;0 172 | -------------------------------------------------------------------------------- /content/breast-cancer/breast-cancer.csv: -------------------------------------------------------------------------------- 1 | age,menopause,tumor-size,inv-nodes,node-caps,deg-malig,breast,breast-quad,irradiat,Class 2 | 40-49,premeno,15-19,0-2,yes,3,right,left_up,no,recurrence-events 3 | 50-59,ge40,15-19,0-2,no,1,right,central,no,no-recurrence-events 4 | 50-59,ge40,35-39,0-2,no,2,left,left_low,no,recurrence-events 5 | 40-49,premeno,35-39,0-2,yes,3,right,left_low,yes,no-recurrence-events 6 | 40-49,premeno,30-34,3-5,yes,2,left,right_up,no,recurrence-events 7 | 50-59,premeno,25-29,3-5,no,2,right,left_up,yes,no-recurrence-events 8 | 50-59,ge40,40-44,0-2,no,3,left,left_up,no,no-recurrence-events 9 | 40-49,premeno,10-14,0-2,no,2,left,left_up,no,no-recurrence-events 10 | 40-49,premeno,0-4,0-2,no,2,right,right_low,no,no-recurrence-events 11 | 40-49,ge40,40-44,15-17,yes,2,right,left_up,yes,no-recurrence-events 12 | 50-59,premeno,25-29,0-2,no,2,left,left_low,no,no-recurrence-events 13 | 60-69,ge40,15-19,0-2,no,2,right,left_up,no,no-recurrence-events 14 | 50-59,ge40,30-34,0-2,no,1,right,central,no,no-recurrence-events 15 | 50-59,ge40,25-29,0-2,no,2,right,left_up,no,no-recurrence-events 16 | 40-49,premeno,25-29,0-2,no,2,left,left_low,yes,recurrence-events 17 | 30-39,premeno,20-24,0-2,no,3,left,central,no,no-recurrence-events 18 | 50-59,premeno,10-14,3-5,no,1,right,left_up,no,no-recurrence-events 19 | 60-69,ge40,15-19,0-2,no,2,right,left_up,no,no-recurrence-events 20 | 50-59,premeno,40-44,0-2,no,2,left,left_up,no,no-recurrence-events 21 | 50-59,ge40,20-24,0-2,no,3,left,left_up,no,no-recurrence-events 22 | 50-59,lt40,20-24,0-2,?,1,left,left_low,no,recurrence-events 23 | 60-69,ge40,40-44,3-5,no,2,right,left_up,yes,no-recurrence-events 24 | 50-59,ge40,15-19,0-2,no,2,right,left_low,no,no-recurrence-events 25 | 40-49,premeno,10-14,0-2,no,1,right,left_up,no,no-recurrence-events 26 | 30-39,premeno,15-19,6-8,yes,3,left,left_low,yes,recurrence-events 27 | 50-59,ge40,20-24,3-5,yes,2,right,left_up,no,no-recurrence-events 28 | 50-59,ge40,10-14,0-2,no,2,right,left_low,no,no-recurrence-events 29 | 40-49,premeno,10-14,0-2,no,1,right,left_up,no,no-recurrence-events 30 | 60-69,ge40,30-34,3-5,yes,3,left,left_low,no,no-recurrence-events 31 | 40-49,premeno,15-19,15-17,yes,3,left,left_low,no,recurrence-events 32 | 60-69,ge40,30-34,0-2,no,3,right,central,no,recurrence-events 33 | 60-69,ge40,25-29,3-5,?,1,right,left_low,yes,no-recurrence-events 34 | 50-59,ge40,25-29,0-2,no,3,left,right_up,no,no-recurrence-events 35 | 50-59,ge40,20-24,0-2,no,3,right,left_up,no,no-recurrence-events 36 | 40-49,premeno,30-34,0-2,no,1,left,left_low,yes,recurrence-events 37 | 30-39,premeno,15-19,0-2,no,1,left,left_low,no,no-recurrence-events 38 | 40-49,premeno,10-14,0-2,no,2,right,left_up,no,no-recurrence-events 39 | 60-69,ge40,45-49,6-8,yes,3,left,central,no,no-recurrence-events 40 | 40-49,ge40,20-24,0-2,no,3,left,left_low,no,no-recurrence-events 41 | 40-49,premeno,10-14,0-2,no,1,right,right_low,no,no-recurrence-events 42 | 30-39,premeno,35-39,0-2,no,3,left,left_low,no,recurrence-events 43 | 40-49,premeno,35-39,9-11,yes,2,right,right_up,yes,no-recurrence-events 44 | 60-69,ge40,25-29,0-2,no,2,right,left_low,no,no-recurrence-events 45 | 50-59,ge40,20-24,3-5,yes,3,right,right_up,no,recurrence-events 46 | 30-39,premeno,15-19,0-2,no,1,left,left_low,no,no-recurrence-events 47 | 50-59,premeno,30-34,0-2,no,3,left,right_up,no,recurrence-events 48 | 60-69,ge40,10-14,0-2,no,2,right,left_up,yes,no-recurrence-events 49 | 40-49,premeno,35-39,0-2,yes,3,right,left_up,yes,no-recurrence-events 50 | 50-59,premeno,50-54,0-2,yes,2,right,left_up,yes,no-recurrence-events 51 | 50-59,ge40,40-44,0-2,no,3,right,left_up,no,no-recurrence-events 52 | 70-79,ge40,15-19,9-11,?,1,left,left_low,yes,recurrence-events 53 | 50-59,lt40,30-34,0-2,no,3,right,left_up,no,no-recurrence-events 54 | 40-49,premeno,0-4,0-2,no,3,left,central,no,no-recurrence-events 55 | 70-79,ge40,40-44,0-2,no,1,right,right_up,no,no-recurrence-events 56 | 40-49,premeno,25-29,0-2,?,2,left,right_low,yes,no-recurrence-events 57 | 50-59,ge40,25-29,15-17,yes,3,right,left_up,no,no-recurrence-events 58 | 50-59,premeno,20-24,0-2,no,1,left,left_low,no,no-recurrence-events 59 | 50-59,ge40,35-39,15-17,no,3,left,left_low,no,no-recurrence-events 60 | 50-59,ge40,50-54,0-2,no,1,right,right_up,no,no-recurrence-events 61 | 30-39,premeno,0-4,0-2,no,2,right,central,no,recurrence-events 62 | 50-59,ge40,40-44,6-8,yes,3,left,left_low,yes,recurrence-events 63 | 40-49,premeno,30-34,0-2,no,2,right,right_up,yes,no-recurrence-events 64 | 40-49,ge40,20-24,0-2,no,3,left,left_up,no,no-recurrence-events 65 | 40-49,premeno,30-34,15-17,yes,3,left,left_low,no,recurrence-events 66 | 40-49,ge40,20-24,0-2,no,2,right,left_up,no,recurrence-events 67 | 50-59,ge40,15-19,0-2,no,1,right,central,no,no-recurrence-events 68 | 30-39,premeno,25-29,0-2,no,2,right,left_low,no,no-recurrence-events 69 | 60-69,ge40,15-19,0-2,no,2,left,left_low,no,no-recurrence-events 70 | 50-59,premeno,50-54,9-11,yes,2,right,left_up,no,recurrence-events 71 | 30-39,premeno,10-14,0-2,no,1,right,left_low,no,no-recurrence-events 72 | 50-59,premeno,25-29,3-5,yes,3,left,left_low,yes,recurrence-events 73 | 60-69,ge40,25-29,3-5,?,1,right,left_up,yes,no-recurrence-events 74 | 60-69,ge40,10-14,0-2,no,1,right,left_low,no,no-recurrence-events 75 | 50-59,ge40,30-34,6-8,yes,3,left,right_low,no,recurrence-events 76 | 30-39,premeno,25-29,6-8,yes,3,left,right_low,yes,recurrence-events 77 | 50-59,ge40,10-14,0-2,no,1,left,left_low,no,no-recurrence-events 78 | 50-59,premeno,15-19,0-2,no,1,left,left_low,no,no-recurrence-events 79 | 40-49,premeno,25-29,0-2,no,2,right,central,no,no-recurrence-events 80 | 40-49,premeno,25-29,0-2,no,3,left,right_up,no,recurrence-events 81 | 60-69,ge40,30-34,6-8,yes,2,right,right_up,no,no-recurrence-events 82 | 50-59,lt40,15-19,0-2,no,2,left,left_low,no,no-recurrence-events 83 | 40-49,premeno,25-29,0-2,no,2,right,left_low,no,no-recurrence-events 84 | 40-49,premeno,30-34,0-2,no,1,right,left_up,no,no-recurrence-events 85 | 60-69,ge40,15-19,0-2,no,2,left,left_up,yes,no-recurrence-events 86 | 30-39,premeno,0-4,0-2,no,2,right,central,no,no-recurrence-events 87 | 50-59,ge40,35-39,0-2,no,3,left,left_up,no,no-recurrence-events 88 | 40-49,premeno,40-44,0-2,no,1,right,left_up,no,no-recurrence-events 89 | 30-39,premeno,25-29,6-8,yes,2,right,left_up,yes,no-recurrence-events 90 | 50-59,ge40,20-24,0-2,no,1,right,left_low,no,no-recurrence-events 91 | 50-59,ge40,30-34,0-2,no,1,left,left_up,no,no-recurrence-events 92 | 60-69,ge40,20-24,0-2,no,1,right,left_up,no,recurrence-events 93 | 30-39,premeno,30-34,3-5,no,3,right,left_up,yes,recurrence-events 94 | 50-59,lt40,20-24,0-2,?,1,left,left_up,no,recurrence-events 95 | 50-59,premeno,10-14,0-2,no,2,right,left_up,no,no-recurrence-events 96 | 50-59,ge40,20-24,0-2,no,2,right,left_up,no,no-recurrence-events 97 | 40-49,premeno,45-49,0-2,no,2,left,left_low,yes,no-recurrence-events 98 | 30-39,premeno,40-44,0-2,no,1,left,left_up,no,recurrence-events 99 | 50-59,premeno,10-14,0-2,no,1,left,left_low,no,no-recurrence-events 100 | 60-69,ge40,30-34,0-2,no,3,right,left_up,yes,recurrence-events 101 | 40-49,premeno,35-39,0-2,no,1,right,left_up,no,recurrence-events 102 | 40-49,premeno,20-24,3-5,yes,2,left,left_low,yes,recurrence-events 103 | 50-59,premeno,15-19,0-2,no,2,left,left_low,no,recurrence-events 104 | 50-59,ge40,30-34,0-2,no,3,right,left_low,no,no-recurrence-events 105 | 60-69,ge40,20-24,0-2,no,2,left,left_up,no,no-recurrence-events 106 | 40-49,premeno,20-24,0-2,no,1,left,right_low,no,no-recurrence-events 107 | 60-69,ge40,30-34,3-5,yes,2,left,central,yes,recurrence-events 108 | 60-69,ge40,20-24,3-5,no,2,left,left_low,yes,recurrence-events 109 | 50-59,premeno,25-29,0-2,no,2,left,right_up,no,recurrence-events 110 | 50-59,ge40,30-34,0-2,no,1,right,right_up,no,no-recurrence-events 111 | 40-49,premeno,20-24,0-2,no,2,left,right_low,no,no-recurrence-events 112 | 60-69,ge40,15-19,0-2,no,1,right,left_up,no,no-recurrence-events 113 | 60-69,ge40,30-34,0-2,no,2,left,left_low,yes,no-recurrence-events 114 | 30-39,premeno,30-34,0-2,no,2,left,left_up,no,no-recurrence-events 115 | 30-39,premeno,40-44,3-5,no,3,right,right_up,yes,no-recurrence-events 116 | 60-69,ge40,5-9,0-2,no,1,left,central,no,no-recurrence-events 117 | 60-69,ge40,10-14,0-2,no,1,left,left_up,no,no-recurrence-events 118 | 40-49,premeno,30-34,6-8,yes,3,right,left_up,no,recurrence-events 119 | 60-69,ge40,10-14,0-2,no,1,left,left_up,no,no-recurrence-events 120 | 40-49,premeno,35-39,9-11,yes,2,right,left_up,yes,no-recurrence-events 121 | 40-49,premeno,20-24,0-2,no,1,right,left_low,no,no-recurrence-events 122 | 40-49,premeno,30-34,0-2,yes,3,right,right_up,no,recurrence-events 123 | 50-59,premeno,25-29,0-2,yes,2,left,left_up,no,no-recurrence-events 124 | 40-49,premeno,15-19,0-2,no,2,left,left_low,no,no-recurrence-events 125 | 30-39,premeno,35-39,9-11,yes,3,left,left_low,no,recurrence-events 126 | 30-39,premeno,10-14,0-2,no,2,left,right_low,no,no-recurrence-events 127 | 50-59,ge40,30-34,0-2,no,1,right,left_low,no,no-recurrence-events 128 | 60-69,ge40,30-34,0-2,no,2,left,left_up,no,no-recurrence-events 129 | 60-69,ge40,25-29,0-2,no,2,left,left_low,no,no-recurrence-events 130 | 40-49,premeno,15-19,0-2,no,2,left,left_up,no,recurrence-events 131 | 60-69,ge40,15-19,0-2,no,2,right,left_low,no,no-recurrence-events 132 | 40-49,premeno,30-34,0-2,no,2,left,right_low,no,no-recurrence-events 133 | 20-29,premeno,35-39,0-2,no,2,right,right_up,no,no-recurrence-events 134 | 40-49,premeno,30-34,0-2,no,3,right,right_up,no,recurrence-events 135 | 40-49,premeno,25-29,0-2,no,2,right,left_low,no,recurrence-events 136 | 30-39,premeno,30-34,0-2,no,3,left,left_low,no,no-recurrence-events 137 | 30-39,premeno,15-19,0-2,no,1,right,left_low,no,recurrence-events 138 | 50-59,ge40,0-4,0-2,no,1,right,central,no,no-recurrence-events 139 | 50-59,ge40,0-4,0-2,no,1,left,left_low,no,no-recurrence-events 140 | 60-69,ge40,50-54,0-2,no,3,right,left_up,no,recurrence-events 141 | 50-59,premeno,30-34,0-2,no,1,left,central,no,no-recurrence-events 142 | 60-69,ge40,20-24,24-26,yes,3,left,left_low,yes,recurrence-events 143 | 40-49,premeno,25-29,0-2,no,2,left,left_up,no,no-recurrence-events 144 | 40-49,premeno,30-34,3-5,no,2,right,left_up,no,recurrence-events 145 | 50-59,premeno,20-24,3-5,yes,2,left,left_low,no,no-recurrence-events 146 | 50-59,ge40,15-19,0-2,yes,2,left,central,yes,no-recurrence-events 147 | 50-59,premeno,10-14,0-2,no,3,left,left_low,no,no-recurrence-events 148 | 30-39,premeno,30-34,9-11,no,2,right,left_up,yes,recurrence-events 149 | 60-69,ge40,10-14,0-2,no,1,left,left_low,no,no-recurrence-events 150 | 40-49,premeno,40-44,0-2,no,2,right,left_low,no,no-recurrence-events 151 | 50-59,ge40,30-34,9-11,?,3,left,left_up,yes,no-recurrence-events 152 | 40-49,premeno,50-54,0-2,no,2,right,left_low,yes,recurrence-events 153 | 50-59,ge40,15-19,0-2,no,2,right,right_up,no,no-recurrence-events 154 | 50-59,ge40,40-44,3-5,yes,2,left,left_low,no,no-recurrence-events 155 | 30-39,premeno,25-29,3-5,yes,3,left,left_low,yes,recurrence-events 156 | 60-69,ge40,10-14,0-2,no,2,left,left_low,no,no-recurrence-events 157 | 60-69,lt40,10-14,0-2,no,1,left,right_up,no,no-recurrence-events 158 | 30-39,premeno,30-34,0-2,no,2,left,left_up,no,recurrence-events 159 | 30-39,premeno,20-24,3-5,yes,2,left,left_low,no,recurrence-events 160 | 50-59,ge40,10-14,0-2,no,1,right,left_up,no,no-recurrence-events 161 | 60-69,ge40,25-29,0-2,no,3,right,left_up,no,no-recurrence-events 162 | 50-59,ge40,25-29,3-5,yes,3,right,left_up,no,no-recurrence-events 163 | 40-49,premeno,30-34,6-8,no,2,left,left_up,no,no-recurrence-events 164 | 60-69,ge40,50-54,0-2,no,2,left,left_low,no,no-recurrence-events 165 | 50-59,premeno,30-34,0-2,no,3,left,left_low,no,no-recurrence-events 166 | 40-49,ge40,20-24,3-5,no,3,right,left_low,yes,recurrence-events 167 | 50-59,ge40,30-34,6-8,yes,2,left,right_low,yes,recurrence-events 168 | 60-69,ge40,25-29,3-5,no,2,right,right_up,no,recurrence-events 169 | 40-49,premeno,20-24,0-2,no,2,left,central,no,no-recurrence-events 170 | 40-49,premeno,20-24,0-2,no,2,left,left_up,no,no-recurrence-events 171 | 40-49,premeno,50-54,0-2,no,2,left,left_low,no,no-recurrence-events 172 | 50-59,ge40,20-24,0-2,no,2,right,central,no,recurrence-events 173 | 50-59,ge40,30-34,3-5,no,3,right,left_up,no,recurrence-events 174 | 40-49,ge40,25-29,0-2,no,2,left,left_low,no,no-recurrence-events 175 | 50-59,premeno,25-29,0-2,no,1,right,left_up,no,recurrence-events 176 | 40-49,premeno,40-44,3-5,yes,3,right,left_up,yes,no-recurrence-events 177 | 40-49,premeno,20-24,0-2,no,2,right,left_up,no,no-recurrence-events 178 | 40-49,premeno,20-24,3-5,no,2,right,left_up,no,no-recurrence-events 179 | 40-49,premeno,25-29,9-11,yes,3,right,left_up,no,recurrence-events 180 | 40-49,premeno,25-29,0-2,no,2,right,left_low,no,recurrence-events 181 | 40-49,premeno,20-24,0-2,no,1,right,right_up,no,no-recurrence-events 182 | 30-39,premeno,40-44,0-2,no,2,right,right_up,no,no-recurrence-events 183 | 60-69,ge40,10-14,6-8,yes,3,left,left_up,yes,recurrence-events 184 | 40-49,premeno,35-39,0-2,no,1,left,left_low,no,no-recurrence-events 185 | 50-59,ge40,30-34,3-5,no,3,left,left_low,no,recurrence-events 186 | 40-49,premeno,5-9,0-2,no,1,left,left_low,yes,no-recurrence-events 187 | 60-69,ge40,15-19,0-2,no,1,left,right_low,no,no-recurrence-events 188 | 40-49,premeno,30-34,0-2,no,3,right,right_up,no,no-recurrence-events 189 | 40-49,premeno,25-29,0-2,no,3,left,left_up,no,recurrence-events 190 | 50-59,ge40,5-9,0-2,no,2,right,right_up,no,no-recurrence-events 191 | 50-59,premeno,25-29,0-2,no,2,right,right_low,no,no-recurrence-events 192 | 50-59,premeno,25-29,0-2,no,2,left,right_up,no,recurrence-events 193 | 40-49,premeno,10-14,0-2,no,2,left,left_low,yes,no-recurrence-events 194 | 60-69,ge40,35-39,6-8,yes,3,left,left_low,no,recurrence-events 195 | 60-69,ge40,50-54,0-2,no,2,right,left_up,yes,no-recurrence-events 196 | 40-49,premeno,25-29,0-2,no,2,right,left_up,no,no-recurrence-events 197 | 30-39,premeno,20-24,3-5,no,2,right,central,no,no-recurrence-events 198 | 30-39,premeno,30-34,0-2,no,1,right,left_up,no,recurrence-events 199 | 60-69,lt40,30-34,0-2,no,1,left,left_low,no,no-recurrence-events 200 | 40-49,premeno,15-19,12-14,no,3,right,right_low,yes,no-recurrence-events 201 | 60-69,ge40,20-24,0-2,no,3,right,left_low,no,recurrence-events 202 | 30-39,premeno,5-9,0-2,no,2,left,right_low,no,no-recurrence-events 203 | 40-49,premeno,30-34,0-2,no,3,left,left_up,no,no-recurrence-events 204 | 60-69,ge40,30-34,0-2,no,3,left,left_low,no,no-recurrence-events 205 | 40-49,premeno,25-29,0-2,no,1,right,right_low,no,no-recurrence-events 206 | 40-49,premeno,25-29,0-2,no,1,left,right_low,no,no-recurrence-events 207 | 60-69,ge40,40-44,3-5,yes,3,right,left_low,no,recurrence-events 208 | 50-59,ge40,25-29,0-2,no,2,left,left_low,no,no-recurrence-events 209 | 50-59,premeno,30-34,0-2,no,3,right,left_up,yes,recurrence-events 210 | 40-49,ge40,30-34,3-5,no,3,left,left_low,no,recurrence-events 211 | 40-49,premeno,25-29,0-2,no,1,right,left_low,yes,no-recurrence-events 212 | 40-49,ge40,25-29,12-14,yes,3,left,right_low,yes,recurrence-events 213 | 40-49,premeno,40-44,0-2,no,1,left,left_low,no,recurrence-events 214 | 40-49,premeno,20-24,0-2,no,2,left,left_low,no,no-recurrence-events 215 | 50-59,ge40,25-29,0-2,no,1,left,right_low,no,no-recurrence-events 216 | 40-49,premeno,20-24,0-2,no,2,right,left_up,no,no-recurrence-events 217 | 70-79,ge40,40-44,0-2,no,1,right,left_up,no,no-recurrence-events 218 | 60-69,ge40,25-29,0-2,no,3,left,left_up,no,recurrence-events 219 | 50-59,premeno,25-29,0-2,no,2,left,left_low,no,no-recurrence-events 220 | 60-69,ge40,45-49,0-2,no,1,right,right_up,yes,recurrence-events 221 | 50-59,ge40,20-24,0-2,yes,2,right,left_up,no,no-recurrence-events 222 | 50-59,ge40,25-29,0-2,no,1,left,left_low,no,no-recurrence-events 223 | 50-59,ge40,20-24,0-2,no,3,left,left_up,no,no-recurrence-events 224 | 40-49,premeno,20-24,3-5,no,2,right,left_low,no,no-recurrence-events 225 | 50-59,ge40,35-39,0-2,no,2,left,left_up,no,no-recurrence-events 226 | 30-39,premeno,20-24,0-2,no,3,left,left_up,yes,recurrence-events 227 | 60-69,ge40,30-34,0-2,no,1,right,left_up,no,no-recurrence-events 228 | 60-69,ge40,25-29,0-2,no,3,right,left_low,no,no-recurrence-events 229 | 40-49,ge40,30-34,0-2,no,2,left,left_up,yes,no-recurrence-events 230 | 30-39,premeno,25-29,0-2,no,2,left,left_low,no,no-recurrence-events 231 | 40-49,premeno,20-24,0-2,no,2,left,left_low,no,recurrence-events 232 | 30-39,premeno,20-24,0-2,no,2,left,right_low,no,no-recurrence-events 233 | 40-49,premeno,10-14,0-2,no,2,right,left_low,no,no-recurrence-events 234 | 50-59,premeno,15-19,0-2,no,2,right,right_low,no,no-recurrence-events 235 | 50-59,premeno,25-29,0-2,no,1,right,left_up,no,no-recurrence-events 236 | 60-69,ge40,20-24,0-2,no,2,right,left_up,no,no-recurrence-events 237 | 60-69,ge40,40-44,0-2,no,2,right,left_low,no,recurrence-events 238 | 30-39,lt40,15-19,0-2,no,3,right,left_up,no,no-recurrence-events 239 | 40-49,premeno,30-34,12-14,yes,3,left,left_up,yes,recurrence-events 240 | 60-69,ge40,30-34,0-2,yes,2,right,right_up,yes,recurrence-events 241 | 50-59,ge40,40-44,6-8,yes,3,left,left_low,yes,recurrence-events 242 | 50-59,ge40,30-34,0-2,no,3,left,?,no,recurrence-events 243 | 70-79,ge40,10-14,0-2,no,2,left,central,no,no-recurrence-events 244 | 30-39,premeno,40-44,0-2,no,2,left,left_low,yes,no-recurrence-events 245 | 40-49,premeno,30-34,0-2,no,2,right,right_low,no,no-recurrence-events 246 | 40-49,premeno,30-34,0-2,no,1,left,left_low,no,no-recurrence-events 247 | 60-69,ge40,15-19,0-2,no,2,left,left_low,no,no-recurrence-events 248 | 40-49,premeno,10-14,0-2,no,2,left,left_low,no,no-recurrence-events 249 | 60-69,ge40,20-24,0-2,no,1,left,left_low,no,no-recurrence-events 250 | 50-59,ge40,10-14,0-2,no,1,left,left_up,no,no-recurrence-events 251 | 50-59,premeno,25-29,0-2,no,1,left,left_low,no,no-recurrence-events 252 | 50-59,ge40,30-34,9-11,yes,3,left,right_low,yes,recurrence-events 253 | 50-59,ge40,10-14,0-2,no,2,left,left_low,no,no-recurrence-events 254 | 40-49,premeno,30-34,0-2,no,1,left,right_up,no,no-recurrence-events 255 | 70-79,ge40,0-4,0-2,no,1,left,right_low,no,no-recurrence-events 256 | 40-49,premeno,25-29,0-2,no,3,right,left_up,yes,no-recurrence-events 257 | 50-59,premeno,25-29,0-2,no,3,right,left_low,yes,recurrence-events 258 | 50-59,ge40,40-44,0-2,no,2,left,left_low,no,no-recurrence-events 259 | 60-69,ge40,25-29,0-2,no,3,left,right_low,yes,recurrence-events 260 | 40-49,premeno,30-34,3-5,yes,2,right,left_low,no,no-recurrence-events 261 | 50-59,ge40,20-24,0-2,no,2,left,left_up,no,recurrence-events 262 | 70-79,ge40,20-24,0-2,no,3,left,left_up,no,no-recurrence-events 263 | 30-39,premeno,25-29,0-2,no,1,left,central,no,no-recurrence-events 264 | 60-69,ge40,30-34,0-2,no,2,left,left_low,no,no-recurrence-events 265 | 40-49,premeno,20-24,3-5,yes,2,right,right_up,yes,recurrence-events 266 | 50-59,ge40,30-34,9-11,?,3,left,left_low,yes,no-recurrence-events 267 | 50-59,ge40,0-4,0-2,no,2,left,central,no,no-recurrence-events 268 | 40-49,premeno,20-24,0-2,no,3,right,left_low,yes,no-recurrence-events 269 | 30-39,premeno,35-39,0-2,no,3,left,left_low,no,recurrence-events 270 | 60-69,ge40,30-34,0-2,no,1,left,left_up,no,no-recurrence-events 271 | 60-69,ge40,20-24,0-2,no,1,left,left_low,no,no-recurrence-events 272 | 50-59,ge40,25-29,6-8,no,3,left,left_low,yes,recurrence-events 273 | 50-59,premeno,35-39,15-17,yes,3,right,right_up,no,recurrence-events 274 | 30-39,premeno,20-24,3-5,yes,2,right,left_up,yes,no-recurrence-events 275 | 40-49,premeno,20-24,6-8,no,2,right,left_low,yes,no-recurrence-events 276 | 50-59,ge40,35-39,0-2,no,3,left,left_low,no,no-recurrence-events 277 | 50-59,premeno,35-39,0-2,no,2,right,left_up,no,no-recurrence-events 278 | 40-49,premeno,25-29,0-2,no,2,left,left_up,yes,no-recurrence-events 279 | 40-49,premeno,35-39,0-2,no,2,right,right_up,no,no-recurrence-events 280 | 50-59,premeno,30-34,3-5,yes,2,left,left_low,yes,no-recurrence-events 281 | 40-49,premeno,20-24,0-2,no,2,right,right_up,no,no-recurrence-events 282 | 60-69,ge40,15-19,0-2,no,3,right,left_up,yes,no-recurrence-events 283 | 50-59,ge40,30-34,6-8,yes,2,left,left_low,no,no-recurrence-events 284 | 50-59,premeno,25-29,3-5,yes,2,left,left_low,yes,no-recurrence-events 285 | 30-39,premeno,30-34,6-8,yes,2,right,right_up,no,no-recurrence-events 286 | 50-59,premeno,15-19,0-2,no,2,right,left_low,no,no-recurrence-events 287 | 50-59,ge40,40-44,0-2,no,3,left,right_up,no,no-recurrence-events 288 | -------------------------------------------------------------------------------- /content/vote/vote.csv: -------------------------------------------------------------------------------- 1 | handicapped-infants,water-project-cost-sharing,adoption-of-the-budget-resolution,physician-fee-freeze,el-salvador-aid,religious-groups-in-schools,anti-satellite-test-ban,aid-to-nicaraguan-contras,mx-missile,immigration,synfuels-corporation-cutback,education-spending,superfund-right-to-sue,crime,duty-free-exports,export-administration-act-south-africa,Class 2 | n,y,n,y,y,y,n,n,n,y,?,y,y,y,n,y,republican 3 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,?,republican 4 | ?,y,y,?,y,y,n,n,n,n,y,n,y,y,n,n,democrat 5 | n,y,y,n,?,y,n,n,n,n,y,n,y,n,n,y,democrat 6 | y,y,y,n,y,y,n,n,n,n,y,?,y,y,y,y,democrat 7 | n,y,y,n,y,y,n,n,n,n,n,n,y,y,y,y,democrat 8 | n,y,n,y,y,y,n,n,n,n,n,n,?,y,y,y,democrat 9 | n,y,n,y,y,y,n,n,n,n,n,n,y,y,?,y,republican 10 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 11 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,?,?,democrat 12 | n,y,n,y,y,n,n,n,n,n,?,?,y,y,n,n,republican 13 | n,y,n,y,y,y,n,n,n,n,y,?,y,y,?,?,republican 14 | n,y,y,n,n,n,y,y,y,n,n,n,y,n,?,?,democrat 15 | y,y,y,n,n,y,y,y,?,y,y,?,n,n,y,?,democrat 16 | n,y,n,y,y,y,n,n,n,n,n,y,?,?,n,?,republican 17 | n,y,n,y,y,y,n,n,n,y,n,y,y,?,n,?,republican 18 | y,n,y,n,n,y,n,y,?,y,y,y,?,n,n,y,democrat 19 | y,?,y,n,n,n,y,y,y,n,n,n,y,n,y,y,democrat 20 | n,y,n,y,y,y,n,n,n,n,n,?,y,y,n,n,republican 21 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 22 | y,y,y,n,n,?,y,y,n,n,y,n,n,n,y,y,democrat 23 | y,y,y,n,n,n,y,y,y,n,n,n,?,?,y,y,democrat 24 | y,?,y,n,n,n,y,y,y,n,n,?,n,n,y,y,democrat 25 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 26 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 27 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 28 | y,n,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 29 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 30 | y,n,n,y,y,n,y,y,y,n,n,y,y,y,n,y,republican 31 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 32 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 33 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,y,?,democrat 34 | y,y,y,n,n,n,y,y,y,y,n,n,y,n,y,y,democrat 35 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 36 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 37 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 38 | y,?,n,y,y,y,n,n,n,y,n,y,?,y,n,y,republican 39 | y,y,n,y,y,y,n,n,n,n,n,n,y,y,n,y,republican 40 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 41 | y,n,y,n,n,n,y,y,y,y,y,n,y,n,y,y,democrat 42 | y,y,y,n,n,n,y,y,y,n,?,n,n,n,n,?,democrat 43 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 44 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,n,y,democrat 45 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 46 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,n,?,democrat 47 | y,y,y,n,n,n,y,y,?,n,y,n,n,n,y,?,democrat 48 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,n,y,democrat 49 | y,n,y,n,n,n,y,y,?,n,n,n,n,n,n,?,democrat 50 | y,y,y,n,n,n,y,y,n,n,n,n,n,y,n,y,democrat 51 | n,?,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 52 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 53 | n,y,n,y,y,y,n,?,n,n,n,y,y,y,n,y,republican 54 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,?,?,democrat 55 | y,y,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 56 | y,y,y,n,n,y,?,y,n,n,y,y,n,y,n,?,democrat 57 | n,y,n,y,y,y,n,n,n,y,y,y,y,y,n,n,republican 58 | n,y,n,y,y,y,n,n,n,y,y,y,y,y,n,y,republican 59 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 60 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 61 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,?,republican 62 | y,y,y,n,n,?,y,y,y,y,n,n,n,n,y,?,democrat 63 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 64 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,n,?,democrat 65 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,n,y,democrat 66 | y,y,y,n,n,n,y,y,y,n,y,?,n,n,n,y,democrat 67 | y,y,n,y,y,y,y,n,n,n,n,y,y,y,n,y,republican 68 | n,y,n,y,y,y,y,n,n,n,y,y,y,y,n,y,republican 69 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 70 | y,?,y,n,n,n,y,y,y,n,n,n,y,n,y,y,democrat 71 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 72 | y,n,y,n,n,n,y,y,y,n,n,n,y,n,y,?,democrat 73 | y,y,y,y,n,n,y,y,y,y,y,n,n,y,n,y,republican 74 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,y,?,democrat 75 | y,n,y,y,y,n,y,n,y,y,n,n,y,y,n,y,republican 76 | y,n,y,n,n,y,y,y,y,y,y,n,n,y,y,y,democrat 77 | n,y,y,y,y,y,n,n,n,y,y,n,y,y,n,n,democrat 78 | n,y,y,n,y,y,n,n,n,y,y,y,y,y,n,?,democrat 79 | n,y,y,y,y,y,n,y,y,y,y,y,y,y,n,y,democrat 80 | y,y,y,n,y,y,n,n,n,y,y,n,y,y,n,y,democrat 81 | n,n,n,y,y,n,n,n,n,y,n,y,y,y,n,n,republican 82 | y,n,y,n,n,y,y,y,y,y,n,y,n,y,n,?,democrat 83 | y,n,y,n,n,n,y,y,?,y,y,y,n,y,n,y,democrat 84 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 85 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 86 | n,?,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 87 | n,n,y,n,y,y,n,n,n,y,y,y,y,y,n,y,democrat 88 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 89 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 90 | n,y,y,n,y,y,y,n,y,y,y,n,y,y,n,y,democrat 91 | n,n,n,y,y,y,n,n,n,y,n,?,y,y,n,?,republican 92 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 93 | y,n,y,n,n,n,y,y,y,y,y,n,n,n,y,y,democrat 94 | y,y,y,n,n,n,y,y,n,y,y,n,n,?,y,y,democrat 95 | y,n,y,n,n,n,y,n,y,y,y,n,n,n,y,y,democrat 96 | y,n,y,n,y,y,n,n,n,n,n,n,n,n,n,y,democrat 97 | y,n,y,n,y,y,n,?,?,n,y,?,?,?,y,y,democrat 98 | n,n,?,n,y,y,n,n,n,n,y,y,y,y,n,y,democrat 99 | y,n,n,n,y,y,y,n,n,y,y,n,n,y,n,y,democrat 100 | y,y,y,n,n,y,y,y,y,y,n,n,n,n,n,y,democrat 101 | n,n,n,y,y,y,n,n,n,y,?,y,y,y,n,n,republican 102 | y,n,n,n,y,y,n,n,n,n,y,y,n,y,n,y,democrat 103 | y,n,y,n,y,y,y,n,n,n,y,n,n,y,n,y,democrat 104 | y,n,y,n,y,y,y,n,?,n,y,n,y,y,y,?,democrat 105 | y,n,n,n,y,y,?,n,?,n,n,n,n,y,?,n,democrat 106 | ?,?,?,?,n,y,y,y,y,y,?,n,y,y,n,?,democrat 107 | y,y,y,n,n,n,n,y,y,n,y,n,n,n,y,y,democrat 108 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 109 | n,?,?,?,?,?,?,?,?,?,?,?,?,y,?,?,republican 110 | y,?,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 111 | y,?,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 112 | n,n,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 113 | n,?,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 114 | n,?,y,n,n,y,y,y,n,y,n,n,n,n,y,?,democrat 115 | n,?,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 116 | y,?,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 117 | n,?,y,n,?,?,y,y,y,y,?,?,n,n,y,y,democrat 118 | y,n,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 119 | y,y,y,y,y,n,y,n,n,n,n,y,y,y,n,y,republican 120 | n,y,y,n,n,n,n,y,y,y,y,n,n,n,y,y,democrat 121 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 122 | n,?,?,y,y,y,n,n,n,y,n,y,y,y,?,y,republican 123 | n,?,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 124 | n,n,n,y,y,y,n,n,n,y,n,y,n,y,n,y,republican 125 | y,?,n,y,y,y,n,y,n,n,n,y,y,y,n,y,republican 126 | n,?,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 127 | n,?,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 128 | n,?,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 129 | n,?,y,n,n,n,y,y,y,y,y,n,n,y,y,y,democrat 130 | n,?,y,n,n,y,n,y,n,y,y,n,n,n,y,y,democrat 131 | ?,?,y,n,n,n,y,y,?,n,?,?,?,?,?,?,democrat 132 | y,?,y,n,?,?,y,y,y,n,n,n,n,n,y,?,democrat 133 | n,n,y,n,n,y,n,y,y,y,n,n,n,y,n,y,democrat 134 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,?,republican 135 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 136 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,?,republican 137 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 138 | n,y,n,y,y,y,n,n,n,y,y,y,y,n,n,y,republican 139 | n,?,y,n,n,y,y,y,y,y,n,n,n,y,y,y,democrat 140 | n,n,y,n,n,y,y,y,y,y,n,n,n,y,n,y,democrat 141 | y,n,y,n,n,y,y,y,y,n,n,n,n,n,y,y,democrat 142 | n,n,n,y,n,n,y,y,y,y,n,n,y,y,n,y,republican 143 | n,n,n,y,y,y,y,y,y,y,n,y,y,y,?,y,republican 144 | n,n,n,y,y,y,y,y,y,y,n,y,y,y,n,y,republican 145 | ?,y,n,n,n,n,y,y,y,y,y,n,n,y,y,y,democrat 146 | n,?,n,n,n,y,y,y,y,y,n,n,n,y,n,?,democrat 147 | n,n,y,n,n,y,y,y,y,y,n,n,n,y,?,y,democrat 148 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 149 | n,n,n,n,n,n,y,y,y,y,n,y,y,y,y,y,democrat 150 | n,y,n,y,y,y,n,n,n,y,y,y,y,y,n,y,republican 151 | n,n,y,n,n,n,y,y,y,y,n,n,y,n,y,y,democrat 152 | y,y,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 153 | y,y,?,y,y,y,n,n,y,n,y,?,y,y,n,n,democrat 154 | n,y,y,n,n,y,n,y,y,y,y,n,y,n,y,y,democrat 155 | n,n,y,n,n,y,y,y,y,y,y,n,y,y,n,y,democrat 156 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 157 | y,y,n,y,y,y,n,?,n,n,y,y,y,y,n,n,republican 158 | y,y,n,y,y,y,y,n,n,n,n,y,y,y,n,n,republican 159 | n,y,y,n,n,y,n,y,y,n,y,n,?,?,?,?,democrat 160 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 161 | n,y,y,n,?,y,y,y,y,y,y,n,n,?,n,?,democrat 162 | n,y,n,n,y,y,n,n,n,n,n,y,y,y,y,y,democrat 163 | n,n,n,n,y,y,y,n,n,n,n,y,y,y,n,y,democrat 164 | n,y,y,n,y,y,y,n,n,n,y,y,y,y,n,y,democrat 165 | n,y,n,y,y,y,y,n,n,n,n,y,y,y,n,y,republican 166 | y,y,n,n,y,y,n,n,n,y,y,y,y,y,n,?,democrat 167 | n,y,y,n,n,y,y,y,y,y,y,n,y,n,y,?,democrat 168 | y,n,y,y,y,y,y,y,n,y,n,y,n,y,y,y,republican 169 | y,n,y,y,y,y,y,y,n,y,y,y,n,y,y,y,republican 170 | n,n,y,y,y,y,n,n,y,n,n,n,y,y,y,?,democrat 171 | y,n,y,n,n,n,y,y,y,y,y,n,n,y,n,y,democrat 172 | y,n,y,n,n,n,?,y,y,?,n,n,n,n,y,?,democrat 173 | n,?,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 174 | n,y,y,n,n,n,y,y,y,y,n,n,?,n,y,y,democrat 175 | n,n,n,n,y,y,n,n,n,y,y,y,y,y,n,y,democrat 176 | y,?,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 177 | n,y,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 178 | n,n,y,y,n,n,y,y,y,y,n,n,n,y,y,y,republican 179 | n,n,y,n,n,n,y,y,y,y,y,?,n,n,y,y,democrat 180 | ?,n,y,n,n,n,y,y,y,y,y,?,n,n,y,?,democrat 181 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 182 | ?,?,y,n,n,n,y,y,y,?,?,n,n,n,?,?,democrat 183 | n,n,y,n,n,n,y,y,y,y,y,n,n,n,y,y,democrat 184 | y,?,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 185 | ?,?,?,?,?,?,?,?,y,?,?,?,?,?,?,?,democrat 186 | n,n,y,n,n,n,y,y,y,y,y,n,n,n,y,y,democrat 187 | y,n,y,n,n,n,y,y,y,y,n,?,n,n,y,y,democrat 188 | n,y,y,n,n,n,y,y,y,y,y,n,n,n,y,y,democrat 189 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 190 | y,?,n,y,y,y,y,y,n,n,n,y,?,y,?,?,republican 191 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 192 | n,?,n,y,y,y,n,n,n,n,n,y,y,y,n,?,republican 193 | n,y,n,y,y,y,n,?,n,y,n,y,y,y,n,?,republican 194 | n,n,n,n,n,y,y,y,y,n,y,n,n,y,y,y,democrat 195 | n,n,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 196 | n,n,y,n,n,y,y,?,y,y,y,n,n,n,y,y,democrat 197 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,?,republican 198 | n,n,y,n,n,y,y,y,y,n,y,y,n,y,y,?,democrat 199 | n,?,y,y,y,y,n,n,n,y,n,n,n,y,n,y,republican 200 | n,n,y,n,n,n,y,y,y,y,y,n,?,n,y,?,democrat 201 | y,y,n,n,n,n,y,y,?,n,y,n,n,n,y,?,democrat 202 | n,n,y,n,n,n,y,y,y,n,n,n,n,y,y,y,democrat 203 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 204 | y,n,y,n,n,y,y,y,y,y,y,n,n,n,y,y,democrat 205 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 206 | n,n,y,y,y,y,y,n,n,n,n,y,y,y,n,y,republican 207 | n,n,y,n,n,y,y,y,y,y,n,y,n,n,n,y,democrat 208 | n,n,n,y,y,y,n,n,n,y,n,y,n,y,n,y,republican 209 | y,?,n,y,y,y,y,n,n,y,n,y,y,y,n,y,republican 210 | n,n,y,n,n,n,y,y,y,n,n,?,n,n,y,y,democrat 211 | y,y,y,n,n,n,y,y,y,y,y,n,n,n,n,y,democrat 212 | n,n,y,n,n,y,y,y,y,n,n,n,n,n,y,y,democrat 213 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 214 | n,n,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 215 | n,y,y,n,n,y,n,y,y,n,y,n,y,n,y,y,democrat 216 | y,y,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 217 | n,y,y,y,y,y,n,n,n,y,y,y,y,y,y,?,democrat 218 | y,y,y,n,y,y,n,n,?,y,n,n,n,y,y,?,democrat 219 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 220 | y,?,y,n,n,n,y,y,y,n,?,n,n,n,y,?,democrat 221 | n,y,y,n,n,n,n,y,y,n,y,n,n,y,y,y,democrat 222 | n,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 223 | n,y,y,n,y,y,n,n,n,n,y,n,n,n,y,?,democrat 224 | y,n,y,n,n,n,y,y,y,n,y,n,n,n,y,?,democrat 225 | n,n,n,y,y,n,n,n,n,n,n,y,y,y,n,y,republican 226 | n,y,n,y,y,y,n,n,n,y,n,?,y,y,n,n,republican 227 | n,?,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 228 | n,n,y,n,n,y,y,y,y,n,y,n,n,y,y,y,democrat 229 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,?,y,democrat 230 | n,y,n,y,y,y,n,n,n,n,n,y,y,?,n,y,republican 231 | n,y,y,y,y,y,y,n,y,y,n,y,y,y,n,y,republican 232 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 233 | n,y,n,y,y,y,n,n,y,y,n,y,y,y,n,y,republican 234 | n,y,y,n,n,n,y,y,n,n,y,n,n,n,y,?,democrat 235 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 236 | n,n,y,n,n,y,y,y,y,y,n,y,n,y,y,?,democrat 237 | n,n,n,y,y,y,n,n,n,y,n,y,n,y,n,y,republican 238 | n,n,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 239 | y,n,y,n,n,y,y,y,n,n,n,y,y,n,n,y,democrat 240 | y,y,y,n,n,n,y,y,?,y,n,n,n,n,y,?,democrat 241 | n,n,n,y,y,y,y,n,n,y,n,n,n,y,y,y,republican 242 | n,n,n,y,n,y,y,?,y,n,n,y,y,y,n,y,republican 243 | y,n,y,n,n,n,y,y,y,y,y,n,n,y,y,y,democrat 244 | n,n,n,n,y,y,y,n,n,n,n,?,n,y,y,y,republican 245 | n,y,y,n,n,n,y,y,?,y,n,n,y,n,y,y,democrat 246 | y,n,y,n,n,n,n,y,y,y,n,n,n,n,y,y,democrat 247 | y,n,y,n,n,n,y,y,y,y,y,n,n,n,y,y,democrat 248 | n,n,y,n,y,n,y,y,y,n,n,n,n,y,?,y,democrat 249 | n,y,n,y,y,y,?,n,n,n,n,?,y,y,n,n,republican 250 | ?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,republican 251 | y,n,y,n,n,n,y,y,?,n,y,n,n,n,y,y,democrat 252 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 253 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 254 | y,y,y,n,n,y,y,y,y,n,n,n,n,n,y,y,democrat 255 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 256 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,n,y,democrat 257 | y,n,y,n,n,n,y,y,y,y,n,n,n,y,y,y,democrat 258 | n,n,n,y,y,n,n,n,n,n,n,y,n,y,n,n,republican 259 | n,n,n,y,y,n,n,n,n,n,n,y,n,y,?,y,republican 260 | n,n,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 261 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,n,y,democrat 262 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,n,y,democrat 263 | y,n,y,n,n,?,y,y,y,n,?,?,n,?,?,?,democrat 264 | y,n,y,n,n,n,y,y,y,y,n,n,?,n,y,y,democrat 265 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 266 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 267 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,n,y,democrat 268 | n,n,n,y,y,y,n,n,n,y,n,y,n,y,n,y,republican 269 | y,n,n,n,n,n,y,y,y,y,n,n,n,y,n,y,republican 270 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 271 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,n,y,democrat 272 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 273 | n,y,y,n,n,y,y,y,y,n,?,n,n,n,n,y,democrat 274 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,y,?,democrat 275 | n,n,n,y,y,n,y,y,n,y,n,y,y,y,?,y,republican 276 | y,n,n,y,y,n,y,n,n,y,n,n,n,y,y,y,republican 277 | n,n,y,n,y,y,n,n,n,n,?,n,y,y,n,n,democrat 278 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,y,n,republican 279 | n,n,y,y,y,y,y,y,n,y,n,n,n,y,n,y,republican 280 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 281 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 282 | n,n,y,n,n,n,y,y,y,y,n,n,n,y,n,y,democrat 283 | y,n,y,y,y,y,y,y,n,n,n,n,n,y,n,?,republican 284 | y,n,n,y,y,y,n,n,n,y,n,?,y,y,n,n,republican 285 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 286 | n,n,y,n,n,y,y,y,y,y,y,n,n,n,?,y,democrat 287 | n,n,y,n,n,y,y,y,y,y,y,n,n,n,y,y,democrat 288 | n,n,y,n,n,y,?,y,?,y,y,y,n,y,y,?,democrat 289 | y,y,y,?,n,y,y,y,y,n,y,n,y,n,?,y,democrat 290 | y,y,y,n,y,y,n,y,n,y,y,n,y,y,y,y,democrat 291 | y,y,y,n,y,y,n,y,n,y,y,n,y,y,n,?,democrat 292 | y,n,y,n,?,y,?,y,y,y,n,n,y,y,n,y,democrat 293 | y,n,y,n,n,y,y,y,y,y,n,?,n,y,n,y,democrat 294 | y,n,y,n,n,y,y,y,n,y,y,n,y,y,y,y,democrat 295 | y,y,y,n,n,y,y,y,y,y,y,n,y,y,y,y,democrat 296 | n,y,y,n,n,y,y,y,n,y,y,n,y,y,n,?,democrat 297 | n,y,n,y,y,y,?,?,n,y,n,y,?,?,?,?,republican 298 | n,n,y,y,y,y,n,n,n,y,n,y,y,y,y,y,republican 299 | y,y,y,n,n,y,y,y,y,y,n,n,?,n,y,?,democrat 300 | n,y,n,n,n,n,y,y,y,y,y,n,n,n,y,y,democrat 301 | n,y,y,n,n,y,y,y,y,y,n,n,y,y,y,y,democrat 302 | n,n,n,y,y,n,y,y,y,y,n,y,y,y,n,y,republican 303 | n,n,?,n,n,y,y,y,y,n,n,n,n,n,y,y,democrat 304 | n,n,n,y,y,y,y,n,n,y,n,y,y,y,n,y,republican 305 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 306 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,?,republican 307 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 308 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 309 | y,n,y,n,n,y,y,y,y,n,n,n,n,y,n,?,democrat 310 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 311 | y,n,n,n,n,y,y,y,y,y,n,n,n,y,y,y,democrat 312 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,y,n,republican 313 | n,n,y,n,n,y,y,y,y,y,n,n,y,n,n,y,democrat 314 | y,y,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 315 | n,y,y,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 316 | n,y,n,y,y,y,y,y,n,n,y,y,y,y,y,y,republican 317 | n,y,y,y,y,y,y,?,n,n,n,n,?,?,y,?,republican 318 | n,n,n,n,n,y,n,y,y,n,y,y,y,y,y,n,democrat 319 | y,n,n,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 320 | n,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 321 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 322 | n,y,y,n,n,y,n,y,y,y,n,n,y,y,n,y,democrat 323 | y,y,y,n,n,n,y,y,y,y,n,n,y,n,n,y,democrat 324 | y,y,y,n,?,y,n,?,n,n,y,n,y,y,n,?,democrat 325 | y,y,y,n,y,y,n,y,?,y,n,n,y,y,n,?,democrat 326 | n,y,n,y,y,y,n,n,n,n,y,y,y,y,n,n,republican 327 | n,y,n,n,y,y,n,n,?,n,n,y,y,y,n,y,democrat 328 | y,y,n,y,n,n,y,y,y,n,y,n,n,y,n,y,democrat 329 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 330 | y,y,y,n,n,n,y,y,y,n,y,n,n,n,n,y,democrat 331 | y,?,y,n,n,y,y,y,y,y,n,n,n,n,y,?,democrat 332 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 333 | y,?,y,n,n,n,y,y,y,n,n,n,n,n,y,?,democrat 334 | y,n,y,n,n,n,y,y,y,n,y,n,n,n,y,?,democrat 335 | n,n,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 336 | n,y,y,n,n,y,y,y,?,n,y,y,n,n,y,y,democrat 337 | n,n,n,y,y,y,n,n,n,y,y,y,y,y,n,?,republican 338 | n,n,y,n,n,y,y,y,n,n,y,n,n,y,?,y,democrat 339 | y,n,y,n,n,n,y,y,y,n,n,n,n,n,y,y,democrat 340 | y,n,y,n,n,n,y,y,y,y,n,n,n,y,y,y,democrat 341 | y,n,n,y,y,y,n,n,n,n,y,y,y,y,n,n,republican 342 | n,n,n,y,y,y,n,n,n,y,y,y,n,y,n,y,republican 343 | n,?,y,?,n,y,y,y,y,y,y,n,?,?,y,y,democrat 344 | n,y,y,n,y,?,y,n,n,y,y,n,y,n,y,y,democrat 345 | n,n,n,y,y,n,y,n,y,y,n,n,n,y,n,y,republican 346 | n,n,y,n,n,n,y,y,y,y,y,n,n,n,y,y,democrat 347 | n,n,n,y,y,y,y,n,n,y,n,y,n,y,y,y,republican 348 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 349 | y,n,n,y,y,y,n,n,n,y,n,y,y,y,n,n,republican 350 | y,n,y,n,n,n,y,y,y,y,n,y,n,n,y,?,democrat 351 | n,y,y,y,y,y,y,y,y,n,n,y,y,y,n,y,republican 352 | n,y,n,n,n,y,y,n,y,n,y,n,n,n,y,y,democrat 353 | n,n,y,y,y,y,y,y,y,y,n,y,y,y,y,y,republican 354 | n,y,n,y,n,y,y,y,y,n,y,n,y,n,y,?,democrat 355 | n,n,y,y,y,y,y,n,n,y,y,y,y,y,n,y,republican 356 | n,y,y,n,n,y,y,y,y,y,n,?,n,n,y,y,democrat 357 | y,n,y,y,n,n,n,y,y,y,n,n,n,y,y,y,republican 358 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 359 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 360 | y,y,y,n,n,y,y,y,y,y,y,y,y,y,n,?,democrat 361 | n,n,n,y,y,y,n,n,n,y,?,y,y,y,n,y,republican 362 | y,n,y,n,n,y,y,y,y,y,n,n,y,n,n,y,democrat 363 | y,n,y,n,y,y,y,n,y,y,n,n,y,y,n,?,democrat 364 | y,y,y,n,n,y,y,y,y,y,y,y,y,n,n,y,democrat 365 | y,y,n,y,y,y,n,n,n,y,y,n,y,n,n,n,republican 366 | y,y,n,y,y,y,n,n,n,n,y,n,y,y,n,y,republican 367 | n,y,n,n,y,y,n,n,n,y,y,n,y,y,n,n,democrat 368 | y,n,y,n,n,n,y,y,n,y,y,n,n,n,n,?,democrat 369 | y,y,y,n,y,y,y,y,n,y,y,n,n,n,y,?,democrat 370 | n,y,y,n,n,y,y,y,n,y,n,n,n,n,y,y,democrat 371 | n,y,n,y,y,y,n,n,n,n,n,n,y,y,n,y,republican 372 | y,y,y,n,?,y,y,y,n,y,?,?,n,n,y,y,democrat 373 | y,y,y,n,?,n,y,y,y,y,n,n,n,n,y,?,democrat 374 | n,y,y,y,y,y,n,n,n,n,y,y,?,y,n,n,democrat 375 | n,y,y,?,y,y,n,y,n,y,?,n,y,y,?,y,democrat 376 | n,y,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 377 | n,y,n,y,y,y,n,n,n,n,y,y,n,y,n,n,democrat 378 | y,?,y,n,n,n,y,y,y,n,y,n,n,n,y,y,democrat 379 | n,y,n,y,y,y,?,?,n,n,?,?,y,?,?,?,republican 380 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 381 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 382 | y,y,y,n,n,y,?,y,y,n,y,n,y,n,y,y,democrat 383 | y,y,y,n,y,y,y,y,y,y,y,n,y,y,n,?,democrat 384 | y,y,n,y,y,y,n,n,n,n,y,n,y,y,n,?,democrat 385 | y,y,y,n,y,y,n,y,y,y,y,n,n,n,n,y,democrat 386 | y,y,y,y,y,y,n,n,n,n,y,y,y,y,n,y,democrat 387 | y,y,n,n,y,y,n,n,n,n,y,y,y,y,y,n,democrat 388 | n,?,y,n,y,y,n,y,n,n,y,n,n,n,n,?,democrat 389 | y,y,y,n,y,y,n,y,y,n,y,n,n,y,n,?,democrat 390 | n,y,y,y,y,y,n,n,n,n,n,y,y,y,n,?,democrat 391 | y,n,y,n,n,n,y,y,y,?,y,n,n,n,y,?,democrat 392 | ?,?,n,n,?,y,?,n,n,n,y,y,n,y,n,?,democrat 393 | y,y,n,n,n,n,n,y,y,n,y,n,n,n,y,n,democrat 394 | y,y,n,y,y,y,n,n,n,n,y,y,y,y,n,y,republican 395 | ?,?,?,?,n,y,n,y,y,n,n,y,y,n,n,?,republican 396 | y,y,?,?,?,y,n,n,n,n,y,n,y,n,n,y,democrat 397 | y,y,y,?,n,n,n,y,n,n,y,?,n,n,y,y,democrat 398 | y,y,y,n,y,y,n,y,n,n,y,n,y,n,y,y,democrat 399 | y,y,n,n,y,?,n,n,n,n,y,n,y,y,n,y,democrat 400 | n,y,y,n,y,y,n,y,n,n,n,n,n,n,n,y,democrat 401 | n,y,n,y,?,y,n,n,n,y,n,y,y,y,n,n,republican 402 | n,y,n,y,y,y,n,?,n,n,?,?,?,y,n,?,republican 403 | n,y,n,y,y,y,n,n,n,y,y,y,y,y,n,n,republican 404 | ?,n,y,y,n,y,y,y,y,y,n,y,n,y,n,y,republican 405 | n,y,n,y,y,y,n,n,n,y,n,y,?,y,n,n,republican 406 | y,y,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 407 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,y,republican 408 | y,n,y,n,y,y,n,n,y,y,n,n,y,y,n,y,democrat 409 | n,n,n,y,y,y,n,n,n,n,y,y,y,y,n,n,democrat 410 | y,n,y,n,n,y,y,y,y,n,n,y,?,y,y,y,democrat 411 | n,n,n,y,y,y,n,n,n,n,n,y,y,y,n,n,republican 412 | n,n,n,y,y,y,n,n,n,n,y,y,y,y,n,y,republican 413 | y,n,y,n,n,y,y,y,y,y,y,n,n,n,n,y,democrat 414 | n,n,n,y,y,y,n,n,n,y,n,y,y,y,n,y,republican 415 | y,y,y,y,y,y,y,y,n,y,?,?,?,y,n,y,republican 416 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,n,y,democrat 417 | n,y,y,n,n,y,y,y,?,y,n,n,n,n,n,y,democrat 418 | y,y,n,y,y,y,n,n,n,y,n,n,y,y,n,y,republican 419 | y,y,y,n,n,n,y,y,y,y,y,n,y,n,n,y,democrat 420 | y,y,y,n,n,n,y,y,n,y,n,n,n,n,n,y,democrat 421 | y,y,y,n,n,n,y,y,y,n,n,n,n,n,n,y,democrat 422 | y,y,y,y,y,y,y,y,n,y,n,n,y,y,n,y,republican 423 | n,y,y,n,y,y,y,y,n,n,y,n,y,n,y,y,democrat 424 | n,n,y,n,n,y,y,y,y,n,y,n,n,n,y,y,democrat 425 | n,y,y,n,n,y,y,y,y,n,y,n,n,y,y,y,democrat 426 | n,y,y,n,n,?,y,y,y,y,y,n,?,y,y,y,democrat 427 | n,n,y,n,n,n,y,y,n,y,y,n,n,n,y,?,democrat 428 | y,n,y,n,n,n,y,y,y,y,n,n,n,n,y,y,democrat 429 | n,n,n,y,y,y,y,y,n,y,n,y,y,y,n,y,republican 430 | ?,?,?,n,n,n,y,y,y,y,n,n,y,n,y,y,democrat 431 | y,n,y,n,?,n,y,y,y,y,n,y,n,?,y,y,democrat 432 | n,n,y,y,y,y,n,n,y,y,n,y,y,y,n,y,republican 433 | n,n,y,n,n,n,y,y,y,y,n,n,n,n,n,y,democrat 434 | n,?,n,y,y,y,n,n,n,n,y,y,y,y,n,y,republican 435 | n,n,n,y,y,y,?,?,?,?,n,y,y,y,n,y,republican 436 | n,y,n,y,y,y,n,n,n,y,n,y,y,y,?,n,republican 437 | -------------------------------------------------------------------------------- /content/breast-cancer/breast-cancer.arff: -------------------------------------------------------------------------------- 1 | % Citation Request: 2 | % This breast cancer domain was obtained from the University Medical Centre, 3 | % Institute of Oncology, Ljubljana, Yugoslavia. Thanks go to M. Zwitter and 4 | % M. Soklic for providing the data. Please include this citation if you plan 5 | % to use this database. 6 | % 7 | % 1. Title: Breast cancer data (Michalski has used this) 8 | % 9 | % 2. Sources: 10 | % -- Matjaz Zwitter & Milan Soklic (physicians) 11 | % Institute of Oncology 12 | % University Medical Center 13 | % Ljubljana, Yugoslavia 14 | % -- Donors: Ming Tan and Jeff Schlimmer (Jeffrey.Schlimmer@a.gp.cs.cmu.edu) 15 | % -- Date: 11 July 1988 16 | % 17 | % 3. Past Usage: (Several: here are some) 18 | % -- Michalski,R.S., Mozetic,I., Hong,J., & Lavrac,N. (1986). The 19 | % Multi-Purpose Incremental Learning System AQ15 and its Testing 20 | % Application to Three Medical Domains. In Proceedings of the 21 | % Fifth National Conference on Artificial Intelligence, 1041-1045, 22 | % Philadelphia, PA: Morgan Kaufmann. 23 | % -- accuracy range: 66%-72% 24 | % -- Clark,P. & Niblett,T. (1987). Induction in Noisy Domains. In 25 | % Progress in Machine Learning (from the Proceedings of the 2nd 26 | % European Working Session on Learning), 11-30, Bled, 27 | % Yugoslavia: Sigma Press. 28 | % -- 8 test results given: 65%-72% accuracy range 29 | % -- Tan, M., & Eshelman, L. (1988). Using weighted networks to 30 | % represent classification knowledge in noisy domains. Proceedings 31 | % of the Fifth International Conference on Machine Learning, 121-134, 32 | % Ann Arbor, MI. 33 | % -- 4 systems tested: accuracy range was 68%-73.5% 34 | % -- Cestnik,G., Konenenko,I, & Bratko,I. (1987). Assistant-86: A 35 | % Knowledge-Elicitation Tool for Sophisticated Users. In I.Bratko 36 | % & N.Lavrac (Eds.) Progress in Machine Learning, 31-45, Sigma Press. 37 | % -- Assistant-86: 78% accuracy 38 | % 39 | % 4. Relevant Information: 40 | % This is one of three domains provided by the Oncology Institute 41 | % that has repeatedly appeared in the machine learning literature. 42 | % (See also lymphography and primary-tumor.) 43 | % 44 | % This data set includes 201 instances of one class and 85 instances of 45 | % another class. The instances are described by 9 attributes, some of 46 | % which are linear and some are nominal. 47 | % 48 | % 5. Number of Instances: 286 49 | % 50 | % 6. Number of Attributes: 9 + the class attribute 51 | % 52 | % 7. Attribute Information: 53 | % 1. Class: no-recurrence-events, recurrence-events 54 | % 2. age: 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, 80-89, 90-99. 55 | % 3. menopause: lt40, ge40, premeno. 56 | % 4. tumor-size: 0-4, 5-9, 10-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 57 | % 45-49, 50-54, 55-59. 58 | % 5. inv-nodes: 0-2, 3-5, 6-8, 9-11, 12-14, 15-17, 18-20, 21-23, 24-26, 59 | % 27-29, 30-32, 33-35, 36-39. 60 | % 6. node-caps: yes, no. 61 | % 7. deg-malig: 1, 2, 3. 62 | % 8. breast: left, right. 63 | % 9. breast-quad: left-up, left-low, right-up, right-low, central. 64 | % 10. irradiat: yes, no. 65 | % 66 | % 8. Missing Attribute Values: (denoted by "?") 67 | % Attribute #: Number of instances with missing values: 68 | % 6. 8 69 | % 9. 1. 70 | % 71 | % 9. Class Distribution: 72 | % 1. no-recurrence-events: 201 instances 73 | % 2. recurrence-events: 85 instances 74 | % 75 | % Num Instances: 286 76 | % Num Attributes: 10 77 | % Num Continuous: 0 (Int 0 / Real 0) 78 | % Num Discrete: 10 79 | % Missing values: 9 / 0.3% 80 | % 81 | % name type enum ints real missing distinct (1) 82 | % 1 'age' Enum 100% 0% 0% 0 / 0% 6 / 2% 0% 83 | % 2 'menopause' Enum 100% 0% 0% 0 / 0% 3 / 1% 0% 84 | % 3 'tumor-size' Enum 100% 0% 0% 0 / 0% 11 / 4% 0% 85 | % 4 'inv-nodes' Enum 100% 0% 0% 0 / 0% 7 / 2% 0% 86 | % 5 'node-caps' Enum 97% 0% 0% 8 / 3% 2 / 1% 0% 87 | % 6 'deg-malig' Enum 100% 0% 0% 0 / 0% 3 / 1% 0% 88 | % 7 'breast' Enum 100% 0% 0% 0 / 0% 2 / 1% 0% 89 | % 8 'breast-quad' Enum 100% 0% 0% 1 / 0% 5 / 2% 0% 90 | % 9 'irradiat' Enum 100% 0% 0% 0 / 0% 2 / 1% 0% 91 | % 10 'Class' Enum 100% 0% 0% 0 / 0% 2 / 1% 0% 92 | % 93 | % 94 | @relation breast-cancer 95 | @attribute age {'10-19','20-29','30-39','40-49','50-59','60-69','70-79','80-89','90-99'} 96 | @attribute menopause {'lt40','ge40','premeno'} 97 | @attribute tumor-size {'0-4','5-9','10-14','15-19','20-24','25-29','30-34','35-39','40-44','45-49','50-54','55-59'} 98 | @attribute inv-nodes {'0-2','3-5','6-8','9-11','12-14','15-17','18-20','21-23','24-26','27-29','30-32','33-35','36-39'} 99 | @attribute node-caps {'yes','no'} 100 | @attribute deg-malig {'1','2','3'} 101 | @attribute breast {'left','right'} 102 | @attribute breast-quad {'left_up','left_low','right_up','right_low','central'} 103 | @attribute 'irradiat' {'yes','no'} 104 | @attribute 'Class' {'no-recurrence-events','recurrence-events'} 105 | @data 106 | '40-49','premeno','15-19','0-2','yes','3','right','left_up','no','recurrence-events' 107 | '50-59','ge40','15-19','0-2','no','1','right','central','no','no-recurrence-events' 108 | '50-59','ge40','35-39','0-2','no','2','left','left_low','no','recurrence-events' 109 | '40-49','premeno','35-39','0-2','yes','3','right','left_low','yes','no-recurrence-events' 110 | '40-49','premeno','30-34','3-5','yes','2','left','right_up','no','recurrence-events' 111 | '50-59','premeno','25-29','3-5','no','2','right','left_up','yes','no-recurrence-events' 112 | '50-59','ge40','40-44','0-2','no','3','left','left_up','no','no-recurrence-events' 113 | '40-49','premeno','10-14','0-2','no','2','left','left_up','no','no-recurrence-events' 114 | '40-49','premeno','0-4','0-2','no','2','right','right_low','no','no-recurrence-events' 115 | '40-49','ge40','40-44','15-17','yes','2','right','left_up','yes','no-recurrence-events' 116 | '50-59','premeno','25-29','0-2','no','2','left','left_low','no','no-recurrence-events' 117 | '60-69','ge40','15-19','0-2','no','2','right','left_up','no','no-recurrence-events' 118 | '50-59','ge40','30-34','0-2','no','1','right','central','no','no-recurrence-events' 119 | '50-59','ge40','25-29','0-2','no','2','right','left_up','no','no-recurrence-events' 120 | '40-49','premeno','25-29','0-2','no','2','left','left_low','yes','recurrence-events' 121 | '30-39','premeno','20-24','0-2','no','3','left','central','no','no-recurrence-events' 122 | '50-59','premeno','10-14','3-5','no','1','right','left_up','no','no-recurrence-events' 123 | '60-69','ge40','15-19','0-2','no','2','right','left_up','no','no-recurrence-events' 124 | '50-59','premeno','40-44','0-2','no','2','left','left_up','no','no-recurrence-events' 125 | '50-59','ge40','20-24','0-2','no','3','left','left_up','no','no-recurrence-events' 126 | '50-59','lt40','20-24','0-2',?,'1','left','left_low','no','recurrence-events' 127 | '60-69','ge40','40-44','3-5','no','2','right','left_up','yes','no-recurrence-events' 128 | '50-59','ge40','15-19','0-2','no','2','right','left_low','no','no-recurrence-events' 129 | '40-49','premeno','10-14','0-2','no','1','right','left_up','no','no-recurrence-events' 130 | '30-39','premeno','15-19','6-8','yes','3','left','left_low','yes','recurrence-events' 131 | '50-59','ge40','20-24','3-5','yes','2','right','left_up','no','no-recurrence-events' 132 | '50-59','ge40','10-14','0-2','no','2','right','left_low','no','no-recurrence-events' 133 | '40-49','premeno','10-14','0-2','no','1','right','left_up','no','no-recurrence-events' 134 | '60-69','ge40','30-34','3-5','yes','3','left','left_low','no','no-recurrence-events' 135 | '40-49','premeno','15-19','15-17','yes','3','left','left_low','no','recurrence-events' 136 | '60-69','ge40','30-34','0-2','no','3','right','central','no','recurrence-events' 137 | '60-69','ge40','25-29','3-5',?,'1','right','left_low','yes','no-recurrence-events' 138 | '50-59','ge40','25-29','0-2','no','3','left','right_up','no','no-recurrence-events' 139 | '50-59','ge40','20-24','0-2','no','3','right','left_up','no','no-recurrence-events' 140 | '40-49','premeno','30-34','0-2','no','1','left','left_low','yes','recurrence-events' 141 | '30-39','premeno','15-19','0-2','no','1','left','left_low','no','no-recurrence-events' 142 | '40-49','premeno','10-14','0-2','no','2','right','left_up','no','no-recurrence-events' 143 | '60-69','ge40','45-49','6-8','yes','3','left','central','no','no-recurrence-events' 144 | '40-49','ge40','20-24','0-2','no','3','left','left_low','no','no-recurrence-events' 145 | '40-49','premeno','10-14','0-2','no','1','right','right_low','no','no-recurrence-events' 146 | '30-39','premeno','35-39','0-2','no','3','left','left_low','no','recurrence-events' 147 | '40-49','premeno','35-39','9-11','yes','2','right','right_up','yes','no-recurrence-events' 148 | '60-69','ge40','25-29','0-2','no','2','right','left_low','no','no-recurrence-events' 149 | '50-59','ge40','20-24','3-5','yes','3','right','right_up','no','recurrence-events' 150 | '30-39','premeno','15-19','0-2','no','1','left','left_low','no','no-recurrence-events' 151 | '50-59','premeno','30-34','0-2','no','3','left','right_up','no','recurrence-events' 152 | '60-69','ge40','10-14','0-2','no','2','right','left_up','yes','no-recurrence-events' 153 | '40-49','premeno','35-39','0-2','yes','3','right','left_up','yes','no-recurrence-events' 154 | '50-59','premeno','50-54','0-2','yes','2','right','left_up','yes','no-recurrence-events' 155 | '50-59','ge40','40-44','0-2','no','3','right','left_up','no','no-recurrence-events' 156 | '70-79','ge40','15-19','9-11',?,'1','left','left_low','yes','recurrence-events' 157 | '50-59','lt40','30-34','0-2','no','3','right','left_up','no','no-recurrence-events' 158 | '40-49','premeno','0-4','0-2','no','3','left','central','no','no-recurrence-events' 159 | '70-79','ge40','40-44','0-2','no','1','right','right_up','no','no-recurrence-events' 160 | '40-49','premeno','25-29','0-2',?,'2','left','right_low','yes','no-recurrence-events' 161 | '50-59','ge40','25-29','15-17','yes','3','right','left_up','no','no-recurrence-events' 162 | '50-59','premeno','20-24','0-2','no','1','left','left_low','no','no-recurrence-events' 163 | '50-59','ge40','35-39','15-17','no','3','left','left_low','no','no-recurrence-events' 164 | '50-59','ge40','50-54','0-2','no','1','right','right_up','no','no-recurrence-events' 165 | '30-39','premeno','0-4','0-2','no','2','right','central','no','recurrence-events' 166 | '50-59','ge40','40-44','6-8','yes','3','left','left_low','yes','recurrence-events' 167 | '40-49','premeno','30-34','0-2','no','2','right','right_up','yes','no-recurrence-events' 168 | '40-49','ge40','20-24','0-2','no','3','left','left_up','no','no-recurrence-events' 169 | '40-49','premeno','30-34','15-17','yes','3','left','left_low','no','recurrence-events' 170 | '40-49','ge40','20-24','0-2','no','2','right','left_up','no','recurrence-events' 171 | '50-59','ge40','15-19','0-2','no','1','right','central','no','no-recurrence-events' 172 | '30-39','premeno','25-29','0-2','no','2','right','left_low','no','no-recurrence-events' 173 | '60-69','ge40','15-19','0-2','no','2','left','left_low','no','no-recurrence-events' 174 | '50-59','premeno','50-54','9-11','yes','2','right','left_up','no','recurrence-events' 175 | '30-39','premeno','10-14','0-2','no','1','right','left_low','no','no-recurrence-events' 176 | '50-59','premeno','25-29','3-5','yes','3','left','left_low','yes','recurrence-events' 177 | '60-69','ge40','25-29','3-5',?,'1','right','left_up','yes','no-recurrence-events' 178 | '60-69','ge40','10-14','0-2','no','1','right','left_low','no','no-recurrence-events' 179 | '50-59','ge40','30-34','6-8','yes','3','left','right_low','no','recurrence-events' 180 | '30-39','premeno','25-29','6-8','yes','3','left','right_low','yes','recurrence-events' 181 | '50-59','ge40','10-14','0-2','no','1','left','left_low','no','no-recurrence-events' 182 | '50-59','premeno','15-19','0-2','no','1','left','left_low','no','no-recurrence-events' 183 | '40-49','premeno','25-29','0-2','no','2','right','central','no','no-recurrence-events' 184 | '40-49','premeno','25-29','0-2','no','3','left','right_up','no','recurrence-events' 185 | '60-69','ge40','30-34','6-8','yes','2','right','right_up','no','no-recurrence-events' 186 | '50-59','lt40','15-19','0-2','no','2','left','left_low','no','no-recurrence-events' 187 | '40-49','premeno','25-29','0-2','no','2','right','left_low','no','no-recurrence-events' 188 | '40-49','premeno','30-34','0-2','no','1','right','left_up','no','no-recurrence-events' 189 | '60-69','ge40','15-19','0-2','no','2','left','left_up','yes','no-recurrence-events' 190 | '30-39','premeno','0-4','0-2','no','2','right','central','no','no-recurrence-events' 191 | '50-59','ge40','35-39','0-2','no','3','left','left_up','no','no-recurrence-events' 192 | '40-49','premeno','40-44','0-2','no','1','right','left_up','no','no-recurrence-events' 193 | '30-39','premeno','25-29','6-8','yes','2','right','left_up','yes','no-recurrence-events' 194 | '50-59','ge40','20-24','0-2','no','1','right','left_low','no','no-recurrence-events' 195 | '50-59','ge40','30-34','0-2','no','1','left','left_up','no','no-recurrence-events' 196 | '60-69','ge40','20-24','0-2','no','1','right','left_up','no','recurrence-events' 197 | '30-39','premeno','30-34','3-5','no','3','right','left_up','yes','recurrence-events' 198 | '50-59','lt40','20-24','0-2',?,'1','left','left_up','no','recurrence-events' 199 | '50-59','premeno','10-14','0-2','no','2','right','left_up','no','no-recurrence-events' 200 | '50-59','ge40','20-24','0-2','no','2','right','left_up','no','no-recurrence-events' 201 | '40-49','premeno','45-49','0-2','no','2','left','left_low','yes','no-recurrence-events' 202 | '30-39','premeno','40-44','0-2','no','1','left','left_up','no','recurrence-events' 203 | '50-59','premeno','10-14','0-2','no','1','left','left_low','no','no-recurrence-events' 204 | '60-69','ge40','30-34','0-2','no','3','right','left_up','yes','recurrence-events' 205 | '40-49','premeno','35-39','0-2','no','1','right','left_up','no','recurrence-events' 206 | '40-49','premeno','20-24','3-5','yes','2','left','left_low','yes','recurrence-events' 207 | '50-59','premeno','15-19','0-2','no','2','left','left_low','no','recurrence-events' 208 | '50-59','ge40','30-34','0-2','no','3','right','left_low','no','no-recurrence-events' 209 | '60-69','ge40','20-24','0-2','no','2','left','left_up','no','no-recurrence-events' 210 | '40-49','premeno','20-24','0-2','no','1','left','right_low','no','no-recurrence-events' 211 | '60-69','ge40','30-34','3-5','yes','2','left','central','yes','recurrence-events' 212 | '60-69','ge40','20-24','3-5','no','2','left','left_low','yes','recurrence-events' 213 | '50-59','premeno','25-29','0-2','no','2','left','right_up','no','recurrence-events' 214 | '50-59','ge40','30-34','0-2','no','1','right','right_up','no','no-recurrence-events' 215 | '40-49','premeno','20-24','0-2','no','2','left','right_low','no','no-recurrence-events' 216 | '60-69','ge40','15-19','0-2','no','1','right','left_up','no','no-recurrence-events' 217 | '60-69','ge40','30-34','0-2','no','2','left','left_low','yes','no-recurrence-events' 218 | '30-39','premeno','30-34','0-2','no','2','left','left_up','no','no-recurrence-events' 219 | '30-39','premeno','40-44','3-5','no','3','right','right_up','yes','no-recurrence-events' 220 | '60-69','ge40','5-9','0-2','no','1','left','central','no','no-recurrence-events' 221 | '60-69','ge40','10-14','0-2','no','1','left','left_up','no','no-recurrence-events' 222 | '40-49','premeno','30-34','6-8','yes','3','right','left_up','no','recurrence-events' 223 | '60-69','ge40','10-14','0-2','no','1','left','left_up','no','no-recurrence-events' 224 | '40-49','premeno','35-39','9-11','yes','2','right','left_up','yes','no-recurrence-events' 225 | '40-49','premeno','20-24','0-2','no','1','right','left_low','no','no-recurrence-events' 226 | '40-49','premeno','30-34','0-2','yes','3','right','right_up','no','recurrence-events' 227 | '50-59','premeno','25-29','0-2','yes','2','left','left_up','no','no-recurrence-events' 228 | '40-49','premeno','15-19','0-2','no','2','left','left_low','no','no-recurrence-events' 229 | '30-39','premeno','35-39','9-11','yes','3','left','left_low','no','recurrence-events' 230 | '30-39','premeno','10-14','0-2','no','2','left','right_low','no','no-recurrence-events' 231 | '50-59','ge40','30-34','0-2','no','1','right','left_low','no','no-recurrence-events' 232 | '60-69','ge40','30-34','0-2','no','2','left','left_up','no','no-recurrence-events' 233 | '60-69','ge40','25-29','0-2','no','2','left','left_low','no','no-recurrence-events' 234 | '40-49','premeno','15-19','0-2','no','2','left','left_up','no','recurrence-events' 235 | '60-69','ge40','15-19','0-2','no','2','right','left_low','no','no-recurrence-events' 236 | '40-49','premeno','30-34','0-2','no','2','left','right_low','no','no-recurrence-events' 237 | '20-29','premeno','35-39','0-2','no','2','right','right_up','no','no-recurrence-events' 238 | '40-49','premeno','30-34','0-2','no','3','right','right_up','no','recurrence-events' 239 | '40-49','premeno','25-29','0-2','no','2','right','left_low','no','recurrence-events' 240 | '30-39','premeno','30-34','0-2','no','3','left','left_low','no','no-recurrence-events' 241 | '30-39','premeno','15-19','0-2','no','1','right','left_low','no','recurrence-events' 242 | '50-59','ge40','0-4','0-2','no','1','right','central','no','no-recurrence-events' 243 | '50-59','ge40','0-4','0-2','no','1','left','left_low','no','no-recurrence-events' 244 | '60-69','ge40','50-54','0-2','no','3','right','left_up','no','recurrence-events' 245 | '50-59','premeno','30-34','0-2','no','1','left','central','no','no-recurrence-events' 246 | '60-69','ge40','20-24','24-26','yes','3','left','left_low','yes','recurrence-events' 247 | '40-49','premeno','25-29','0-2','no','2','left','left_up','no','no-recurrence-events' 248 | '40-49','premeno','30-34','3-5','no','2','right','left_up','no','recurrence-events' 249 | '50-59','premeno','20-24','3-5','yes','2','left','left_low','no','no-recurrence-events' 250 | '50-59','ge40','15-19','0-2','yes','2','left','central','yes','no-recurrence-events' 251 | '50-59','premeno','10-14','0-2','no','3','left','left_low','no','no-recurrence-events' 252 | '30-39','premeno','30-34','9-11','no','2','right','left_up','yes','recurrence-events' 253 | '60-69','ge40','10-14','0-2','no','1','left','left_low','no','no-recurrence-events' 254 | '40-49','premeno','40-44','0-2','no','2','right','left_low','no','no-recurrence-events' 255 | '50-59','ge40','30-34','9-11',?,'3','left','left_up','yes','no-recurrence-events' 256 | '40-49','premeno','50-54','0-2','no','2','right','left_low','yes','recurrence-events' 257 | '50-59','ge40','15-19','0-2','no','2','right','right_up','no','no-recurrence-events' 258 | '50-59','ge40','40-44','3-5','yes','2','left','left_low','no','no-recurrence-events' 259 | '30-39','premeno','25-29','3-5','yes','3','left','left_low','yes','recurrence-events' 260 | '60-69','ge40','10-14','0-2','no','2','left','left_low','no','no-recurrence-events' 261 | '60-69','lt40','10-14','0-2','no','1','left','right_up','no','no-recurrence-events' 262 | '30-39','premeno','30-34','0-2','no','2','left','left_up','no','recurrence-events' 263 | '30-39','premeno','20-24','3-5','yes','2','left','left_low','no','recurrence-events' 264 | '50-59','ge40','10-14','0-2','no','1','right','left_up','no','no-recurrence-events' 265 | '60-69','ge40','25-29','0-2','no','3','right','left_up','no','no-recurrence-events' 266 | '50-59','ge40','25-29','3-5','yes','3','right','left_up','no','no-recurrence-events' 267 | '40-49','premeno','30-34','6-8','no','2','left','left_up','no','no-recurrence-events' 268 | '60-69','ge40','50-54','0-2','no','2','left','left_low','no','no-recurrence-events' 269 | '50-59','premeno','30-34','0-2','no','3','left','left_low','no','no-recurrence-events' 270 | '40-49','ge40','20-24','3-5','no','3','right','left_low','yes','recurrence-events' 271 | '50-59','ge40','30-34','6-8','yes','2','left','right_low','yes','recurrence-events' 272 | '60-69','ge40','25-29','3-5','no','2','right','right_up','no','recurrence-events' 273 | '40-49','premeno','20-24','0-2','no','2','left','central','no','no-recurrence-events' 274 | '40-49','premeno','20-24','0-2','no','2','left','left_up','no','no-recurrence-events' 275 | '40-49','premeno','50-54','0-2','no','2','left','left_low','no','no-recurrence-events' 276 | '50-59','ge40','20-24','0-2','no','2','right','central','no','recurrence-events' 277 | '50-59','ge40','30-34','3-5','no','3','right','left_up','no','recurrence-events' 278 | '40-49','ge40','25-29','0-2','no','2','left','left_low','no','no-recurrence-events' 279 | '50-59','premeno','25-29','0-2','no','1','right','left_up','no','recurrence-events' 280 | '40-49','premeno','40-44','3-5','yes','3','right','left_up','yes','no-recurrence-events' 281 | '40-49','premeno','20-24','0-2','no','2','right','left_up','no','no-recurrence-events' 282 | '40-49','premeno','20-24','3-5','no','2','right','left_up','no','no-recurrence-events' 283 | '40-49','premeno','25-29','9-11','yes','3','right','left_up','no','recurrence-events' 284 | '40-49','premeno','25-29','0-2','no','2','right','left_low','no','recurrence-events' 285 | '40-49','premeno','20-24','0-2','no','1','right','right_up','no','no-recurrence-events' 286 | '30-39','premeno','40-44','0-2','no','2','right','right_up','no','no-recurrence-events' 287 | '60-69','ge40','10-14','6-8','yes','3','left','left_up','yes','recurrence-events' 288 | '40-49','premeno','35-39','0-2','no','1','left','left_low','no','no-recurrence-events' 289 | '50-59','ge40','30-34','3-5','no','3','left','left_low','no','recurrence-events' 290 | '40-49','premeno','5-9','0-2','no','1','left','left_low','yes','no-recurrence-events' 291 | '60-69','ge40','15-19','0-2','no','1','left','right_low','no','no-recurrence-events' 292 | '40-49','premeno','30-34','0-2','no','3','right','right_up','no','no-recurrence-events' 293 | '40-49','premeno','25-29','0-2','no','3','left','left_up','no','recurrence-events' 294 | '50-59','ge40','5-9','0-2','no','2','right','right_up','no','no-recurrence-events' 295 | '50-59','premeno','25-29','0-2','no','2','right','right_low','no','no-recurrence-events' 296 | '50-59','premeno','25-29','0-2','no','2','left','right_up','no','recurrence-events' 297 | '40-49','premeno','10-14','0-2','no','2','left','left_low','yes','no-recurrence-events' 298 | '60-69','ge40','35-39','6-8','yes','3','left','left_low','no','recurrence-events' 299 | '60-69','ge40','50-54','0-2','no','2','right','left_up','yes','no-recurrence-events' 300 | '40-49','premeno','25-29','0-2','no','2','right','left_up','no','no-recurrence-events' 301 | '30-39','premeno','20-24','3-5','no','2','right','central','no','no-recurrence-events' 302 | '30-39','premeno','30-34','0-2','no','1','right','left_up','no','recurrence-events' 303 | '60-69','lt40','30-34','0-2','no','1','left','left_low','no','no-recurrence-events' 304 | '40-49','premeno','15-19','12-14','no','3','right','right_low','yes','no-recurrence-events' 305 | '60-69','ge40','20-24','0-2','no','3','right','left_low','no','recurrence-events' 306 | '30-39','premeno','5-9','0-2','no','2','left','right_low','no','no-recurrence-events' 307 | '40-49','premeno','30-34','0-2','no','3','left','left_up','no','no-recurrence-events' 308 | '60-69','ge40','30-34','0-2','no','3','left','left_low','no','no-recurrence-events' 309 | '40-49','premeno','25-29','0-2','no','1','right','right_low','no','no-recurrence-events' 310 | '40-49','premeno','25-29','0-2','no','1','left','right_low','no','no-recurrence-events' 311 | '60-69','ge40','40-44','3-5','yes','3','right','left_low','no','recurrence-events' 312 | '50-59','ge40','25-29','0-2','no','2','left','left_low','no','no-recurrence-events' 313 | '50-59','premeno','30-34','0-2','no','3','right','left_up','yes','recurrence-events' 314 | '40-49','ge40','30-34','3-5','no','3','left','left_low','no','recurrence-events' 315 | '40-49','premeno','25-29','0-2','no','1','right','left_low','yes','no-recurrence-events' 316 | '40-49','ge40','25-29','12-14','yes','3','left','right_low','yes','recurrence-events' 317 | '40-49','premeno','40-44','0-2','no','1','left','left_low','no','recurrence-events' 318 | '40-49','premeno','20-24','0-2','no','2','left','left_low','no','no-recurrence-events' 319 | '50-59','ge40','25-29','0-2','no','1','left','right_low','no','no-recurrence-events' 320 | '40-49','premeno','20-24','0-2','no','2','right','left_up','no','no-recurrence-events' 321 | '70-79','ge40','40-44','0-2','no','1','right','left_up','no','no-recurrence-events' 322 | '60-69','ge40','25-29','0-2','no','3','left','left_up','no','recurrence-events' 323 | '50-59','premeno','25-29','0-2','no','2','left','left_low','no','no-recurrence-events' 324 | '60-69','ge40','45-49','0-2','no','1','right','right_up','yes','recurrence-events' 325 | '50-59','ge40','20-24','0-2','yes','2','right','left_up','no','no-recurrence-events' 326 | '50-59','ge40','25-29','0-2','no','1','left','left_low','no','no-recurrence-events' 327 | '50-59','ge40','20-24','0-2','no','3','left','left_up','no','no-recurrence-events' 328 | '40-49','premeno','20-24','3-5','no','2','right','left_low','no','no-recurrence-events' 329 | '50-59','ge40','35-39','0-2','no','2','left','left_up','no','no-recurrence-events' 330 | '30-39','premeno','20-24','0-2','no','3','left','left_up','yes','recurrence-events' 331 | '60-69','ge40','30-34','0-2','no','1','right','left_up','no','no-recurrence-events' 332 | '60-69','ge40','25-29','0-2','no','3','right','left_low','no','no-recurrence-events' 333 | '40-49','ge40','30-34','0-2','no','2','left','left_up','yes','no-recurrence-events' 334 | '30-39','premeno','25-29','0-2','no','2','left','left_low','no','no-recurrence-events' 335 | '40-49','premeno','20-24','0-2','no','2','left','left_low','no','recurrence-events' 336 | '30-39','premeno','20-24','0-2','no','2','left','right_low','no','no-recurrence-events' 337 | '40-49','premeno','10-14','0-2','no','2','right','left_low','no','no-recurrence-events' 338 | '50-59','premeno','15-19','0-2','no','2','right','right_low','no','no-recurrence-events' 339 | '50-59','premeno','25-29','0-2','no','1','right','left_up','no','no-recurrence-events' 340 | '60-69','ge40','20-24','0-2','no','2','right','left_up','no','no-recurrence-events' 341 | '60-69','ge40','40-44','0-2','no','2','right','left_low','no','recurrence-events' 342 | '30-39','lt40','15-19','0-2','no','3','right','left_up','no','no-recurrence-events' 343 | '40-49','premeno','30-34','12-14','yes','3','left','left_up','yes','recurrence-events' 344 | '60-69','ge40','30-34','0-2','yes','2','right','right_up','yes','recurrence-events' 345 | '50-59','ge40','40-44','6-8','yes','3','left','left_low','yes','recurrence-events' 346 | '50-59','ge40','30-34','0-2','no','3','left',?,'no','recurrence-events' 347 | '70-79','ge40','10-14','0-2','no','2','left','central','no','no-recurrence-events' 348 | '30-39','premeno','40-44','0-2','no','2','left','left_low','yes','no-recurrence-events' 349 | '40-49','premeno','30-34','0-2','no','2','right','right_low','no','no-recurrence-events' 350 | '40-49','premeno','30-34','0-2','no','1','left','left_low','no','no-recurrence-events' 351 | '60-69','ge40','15-19','0-2','no','2','left','left_low','no','no-recurrence-events' 352 | '40-49','premeno','10-14','0-2','no','2','left','left_low','no','no-recurrence-events' 353 | '60-69','ge40','20-24','0-2','no','1','left','left_low','no','no-recurrence-events' 354 | '50-59','ge40','10-14','0-2','no','1','left','left_up','no','no-recurrence-events' 355 | '50-59','premeno','25-29','0-2','no','1','left','left_low','no','no-recurrence-events' 356 | '50-59','ge40','30-34','9-11','yes','3','left','right_low','yes','recurrence-events' 357 | '50-59','ge40','10-14','0-2','no','2','left','left_low','no','no-recurrence-events' 358 | '40-49','premeno','30-34','0-2','no','1','left','right_up','no','no-recurrence-events' 359 | '70-79','ge40','0-4','0-2','no','1','left','right_low','no','no-recurrence-events' 360 | '40-49','premeno','25-29','0-2','no','3','right','left_up','yes','no-recurrence-events' 361 | '50-59','premeno','25-29','0-2','no','3','right','left_low','yes','recurrence-events' 362 | '50-59','ge40','40-44','0-2','no','2','left','left_low','no','no-recurrence-events' 363 | '60-69','ge40','25-29','0-2','no','3','left','right_low','yes','recurrence-events' 364 | '40-49','premeno','30-34','3-5','yes','2','right','left_low','no','no-recurrence-events' 365 | '50-59','ge40','20-24','0-2','no','2','left','left_up','no','recurrence-events' 366 | '70-79','ge40','20-24','0-2','no','3','left','left_up','no','no-recurrence-events' 367 | '30-39','premeno','25-29','0-2','no','1','left','central','no','no-recurrence-events' 368 | '60-69','ge40','30-34','0-2','no','2','left','left_low','no','no-recurrence-events' 369 | '40-49','premeno','20-24','3-5','yes','2','right','right_up','yes','recurrence-events' 370 | '50-59','ge40','30-34','9-11',?,'3','left','left_low','yes','no-recurrence-events' 371 | '50-59','ge40','0-4','0-2','no','2','left','central','no','no-recurrence-events' 372 | '40-49','premeno','20-24','0-2','no','3','right','left_low','yes','no-recurrence-events' 373 | '30-39','premeno','35-39','0-2','no','3','left','left_low','no','recurrence-events' 374 | '60-69','ge40','30-34','0-2','no','1','left','left_up','no','no-recurrence-events' 375 | '60-69','ge40','20-24','0-2','no','1','left','left_low','no','no-recurrence-events' 376 | '50-59','ge40','25-29','6-8','no','3','left','left_low','yes','recurrence-events' 377 | '50-59','premeno','35-39','15-17','yes','3','right','right_up','no','recurrence-events' 378 | '30-39','premeno','20-24','3-5','yes','2','right','left_up','yes','no-recurrence-events' 379 | '40-49','premeno','20-24','6-8','no','2','right','left_low','yes','no-recurrence-events' 380 | '50-59','ge40','35-39','0-2','no','3','left','left_low','no','no-recurrence-events' 381 | '50-59','premeno','35-39','0-2','no','2','right','left_up','no','no-recurrence-events' 382 | '40-49','premeno','25-29','0-2','no','2','left','left_up','yes','no-recurrence-events' 383 | '40-49','premeno','35-39','0-2','no','2','right','right_up','no','no-recurrence-events' 384 | '50-59','premeno','30-34','3-5','yes','2','left','left_low','yes','no-recurrence-events' 385 | '40-49','premeno','20-24','0-2','no','2','right','right_up','no','no-recurrence-events' 386 | '60-69','ge40','15-19','0-2','no','3','right','left_up','yes','no-recurrence-events' 387 | '50-59','ge40','30-34','6-8','yes','2','left','left_low','no','no-recurrence-events' 388 | '50-59','premeno','25-29','3-5','yes','2','left','left_low','yes','no-recurrence-events' 389 | '30-39','premeno','30-34','6-8','yes','2','right','right_up','no','no-recurrence-events' 390 | '50-59','premeno','15-19','0-2','no','2','right','left_low','no','no-recurrence-events' 391 | '50-59','ge40','40-44','0-2','no','3','left','right_up','no','no-recurrence-events' 392 | % 393 | % 394 | % 395 | --------------------------------------------------------------------------------