├── references ├── Logistic Regression Diagnostics - in R.pdf ├── Logistic Regression Analysis - INTERPRETATION.docx ├── Logistic Regression Diagnostics - Biometry 755.pdf ├── Logistic Regression Diagnostics - Patrick Breheny.pdf └── Diagnostics and model checking for logistic regression.pdf ├── .gitignore ├── README.md ├── datasets ├── Fish.csv ├── Fish_processed.csv ├── Credit.csv ├── Auto.csv ├── Heart.csv └── Insurance.csv ├── data └── train_processed.csv └── Box-Tidwell-Test-in-R.ipynb /references/Logistic Regression Diagnostics - in R.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kennethleungty/Logistic-Regression-Assumptions/HEAD/references/Logistic Regression Diagnostics - in R.pdf -------------------------------------------------------------------------------- /references/Logistic Regression Analysis - INTERPRETATION.docx: -------------------------------------------------------------------------------- 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/references/Diagnostics and model checking for logistic regression.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kennethleungty/Logistic-Regression-Assumptions/HEAD/references/Diagnostics and model checking for logistic regression.pdf -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script 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-------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Assumptions of Logistic Regression, Clearly Explained 2 | #### Understanding and implementing the assumption checks behind one of the most important statistical techniques in data science - Logistic Regression 3 | - Link to TowardsDataScience article: https://towardsdatascience.com/assumptions-of-logistic-regression-clearly-explained-44d85a22b290 4 | - Logistic regression is a highly effective modeling technique that has remained a mainstay in statistics since its development in the 1940s. 5 | - Given its popularity and utility, data practitioners should understand the fundamentals of logistic regression before using it to tackle data and business problems. 6 | - In this project, we explore the key assumptions of logistic regression with theoretical explanations and practical Python implementation of the assumption checks. 7 | ___ 8 | 9 | ### Contents 10 | **(1) Logistic_Regression_Assumptions.ipynb** 11 | - The main notebook containing the Python implementation codes (along with explanations) on how to check for each of the 6 key assumptions in logistic regression 12 | 13 | **(2) Box-Tidwell-Test-in-R.ipynb** 14 | - Notebook containing R code for running Box-Tidwell test (to check for logit linearity assumption) 15 | 16 | **(3) /data** 17 | - Folder containing the public Titanic dataset (train set) 18 | 19 | **(4) /references** 20 | - Folder containing several sets of lecture notes explaining advanced regression 21 | ___ 22 | ### Special Thanks 23 | - @dataninj4 for correcting imports and adding .loc referencing in diagnosis_df cell so that it runs without errors in Python 3.6/3.8 24 | - @ArneTR for rightly pointing out that VIF calculation should include a constant, and correlation matrix should exclude target variable 25 | ___ 26 | 27 | ### References 28 | - [Machine Learning Essentials - Practical Guide in R](http://www.sthda.com/english/articles/36-classification-methods-essentials/148-logistic-regression-assumptions-and-diagnostics-in-r/) 29 | - [Logistic and Linear Regression Assumptions - Violation Recognition and Control](www.lexjansen.com/wuss/2018/130_Final_Paper_PDF.pdf) 30 | - [Testing linearity in the logit using Box-Tidwell Transformation in SPSS - Youtube](https://www.youtube.com/watch?v=sciPFNcYqi8&ab_channel=MikeCrowson) 31 | - [Logistic Regression using SPSS](https://www.researchgate.net/publication/344138306_Logistic_Regression_Using_SPSS) 32 | - [Statistics How To - Cook's Distance](https://www.statisticshowto.com/cooks-distance/) 33 | - [Statsmodels Documentation - GLM](https://www.statsmodels.org/stable/glm.html) 34 | - [Statsmodels Documetation - Logit Influence example notebook](https://www.statsmodels.org/dev/examples/notebooks/generated/influence_glm_logit.html) 35 | - [PennState Eberly College of Science - Stat 462](https://online.stat.psu.edu/stat462/node/173/) 36 | - [Statistics Solution - Assumptions of Logistic Regression](https://bookdown.org/jefftemplewebb/IS-6489/logistic-regression.html#fn40) 37 | - [Course Notes for IS 6489 - Statistics and Predictive Analytics](https://bookdown.org/jefftemplewebb/IS-6489/logistic-regression.html#fn40) 38 | - [MSc in Big Data Analytics at Carlos III University of Madrid - Notes for Predictive Modeling](https://bookdown.org/egarpor/PM-UC3M/) 39 | - [Freakonometrics - Residuals from a Logistic Regression](https://freakonometrics.hypotheses.org/8210) 40 | - [Kaggle - Titanic - Logistic Regression with Python](https://www.kaggle.com/mnassrib/titanic-logistic-regression-with-python) 41 | - [Yellowbrick API Reference - Cook's Distance](https://www.scikit-yb.org/en/latest/api/regressor/influence.html?highlight=cook#module-yellowbrick.regressor.influence) 42 | - [DataCamp - Understanding Logistic Regression in Python](https://www.datacamp.com/community/tutorials/understanding-logistic-regression-python) 43 | - [Statology - How to Calculate Cook's Distance](https://www.statology.org/cooks-distance-python/) 44 | - [ResearchGate - Box-Tidwell Test in SPSS](https://www.researchgate.net/post/What_is_the_correct_way_to_do_Box-Tidwell_test_in_SPSS_for_logistic_regression) 45 | - [CrossValidated - Why include x ln x interaction term helps](https://stats.stackexchange.com/questions/217471/why-does-including-x-lnx-interaction-term-in-logistic-regression-model-helps) 46 | - [UCLA IDRE - Logistic Regression Diagnostics](https://stats.idre.ucla.edu/stata/webbooks/logistic/chapter3/lesson-3-logistic-regression-diagnostics-2/) 47 | - [Logistic and Linear Regression Assumptions: Violation Recognition and Control](https://www.lexjansen.com/wuss/2018/130_Final_Paper_PDF.pdf) 48 | -------------------------------------------------------------------------------- /datasets/Fish.csv: -------------------------------------------------------------------------------- 1 | Species,Weight,Length1,Length2,Length3,Height,Width 2 | Bream,242,23.2,25.4,30,11.52,4.02 3 | Bream,290,24,26.3,31.2,12.48,4.3056 4 | Bream,340,23.9,26.5,31.1,12.3778,4.6961 5 | Bream,363,26.3,29,33.5,12.73,4.4555 6 | Bream,430,26.5,29,34,12.444,5.134 7 | Bream,450,26.8,29.7,34.7,13.6024,4.9274 8 | Bream,500,26.8,29.7,34.5,14.1795,5.2785 9 | Bream,390,27.6,30,35,12.67,4.69 10 | Bream,450,27.6,30,35.1,14.0049,4.8438 11 | Bream,500,28.5,30.7,36.2,14.2266,4.9594 12 | Bream,475,28.4,31,36.2,14.2628,5.1042 13 | Bream,500,28.7,31,36.2,14.3714,4.8146 14 | Bream,500,29.1,31.5,36.4,13.7592,4.368 15 | Bream,340,29.5,32,37.3,13.9129,5.0728 16 | Bream,600,29.4,32,37.2,14.9544,5.1708 17 | Bream,600,29.4,32,37.2,15.438,5.58 18 | Bream,700,30.4,33,38.3,14.8604,5.2854 19 | Bream,700,30.4,33,38.5,14.938,5.1975 20 | Bream,610,30.9,33.5,38.6,15.633,5.1338 21 | Bream,650,31,33.5,38.7,14.4738,5.7276 22 | Bream,575,31.3,34,39.5,15.1285,5.5695 23 | Bream,685,31.4,34,39.2,15.9936,5.3704 24 | Bream,620,31.5,34.5,39.7,15.5227,5.2801 25 | Bream,680,31.8,35,40.6,15.4686,6.1306 26 | Bream,700,31.9,35,40.5,16.2405,5.589 27 | Bream,725,31.8,35,40.9,16.36,6.0532 28 | Bream,720,32,35,40.6,16.3618,6.09 29 | Bream,714,32.7,36,41.5,16.517,5.8515 30 | Bream,850,32.8,36,41.6,16.8896,6.1984 31 | Bream,1000,33.5,37,42.6,18.957,6.603 32 | Bream,920,35,38.5,44.1,18.0369,6.3063 33 | Bream,955,35,38.5,44,18.084,6.292 34 | Bream,925,36.2,39.5,45.3,18.7542,6.7497 35 | Bream,975,37.4,41,45.9,18.6354,6.7473 36 | Bream,950,38,41,46.5,17.6235,6.3705 37 | Roach,40,12.9,14.1,16.2,4.1472,2.268 38 | Roach,69,16.5,18.2,20.3,5.2983,2.8217 39 | Roach,78,17.5,18.8,21.2,5.5756,2.9044 40 | Roach,87,18.2,19.8,22.2,5.6166,3.1746 41 | Roach,120,18.6,20,22.2,6.216,3.5742 42 | Roach,0,19,20.5,22.8,6.4752,3.3516 43 | Roach,110,19.1,20.8,23.1,6.1677,3.3957 44 | Roach,120,19.4,21,23.7,6.1146,3.2943 45 | Roach,150,20.4,22,24.7,5.8045,3.7544 46 | Roach,145,20.5,22,24.3,6.6339,3.5478 47 | Roach,160,20.5,22.5,25.3,7.0334,3.8203 48 | Roach,140,21,22.5,25,6.55,3.325 49 | Roach,160,21.1,22.5,25,6.4,3.8 50 | Roach,169,22,24,27.2,7.5344,3.8352 51 | Roach,161,22,23.4,26.7,6.9153,3.6312 52 | Roach,200,22.1,23.5,26.8,7.3968,4.1272 53 | Roach,180,23.6,25.2,27.9,7.0866,3.906 54 | Roach,290,24,26,29.2,8.8768,4.4968 55 | Roach,272,25,27,30.6,8.568,4.7736 56 | Roach,390,29.5,31.7,35,9.485,5.355 57 | Whitefish,270,23.6,26,28.7,8.3804,4.2476 58 | Whitefish,270,24.1,26.5,29.3,8.1454,4.2485 59 | Whitefish,306,25.6,28,30.8,8.778,4.6816 60 | Whitefish,540,28.5,31,34,10.744,6.562 61 | Whitefish,800,33.7,36.4,39.6,11.7612,6.5736 62 | Whitefish,1000,37.3,40,43.5,12.354,6.525 63 | Parkki,55,13.5,14.7,16.5,6.8475,2.3265 64 | Parkki,60,14.3,15.5,17.4,6.5772,2.3142 65 | Parkki,90,16.3,17.7,19.8,7.4052,2.673 66 | Parkki,120,17.5,19,21.3,8.3922,2.9181 67 | Parkki,150,18.4,20,22.4,8.8928,3.2928 68 | Parkki,140,19,20.7,23.2,8.5376,3.2944 69 | Parkki,170,19,20.7,23.2,9.396,3.4104 70 | Parkki,145,19.8,21.5,24.1,9.7364,3.1571 71 | Parkki,200,21.2,23,25.8,10.3458,3.6636 72 | Parkki,273,23,25,28,11.088,4.144 73 | Parkki,300,24,26,29,11.368,4.234 74 | Perch,5.9,7.5,8.4,8.8,2.112,1.408 75 | Perch,32,12.5,13.7,14.7,3.528,1.9992 76 | Perch,40,13.8,15,16,3.824,2.432 77 | Perch,51.5,15,16.2,17.2,4.5924,2.6316 78 | Perch,70,15.7,17.4,18.5,4.588,2.9415 79 | Perch,100,16.2,18,19.2,5.2224,3.3216 80 | Perch,78,16.8,18.7,19.4,5.1992,3.1234 81 | Perch,80,17.2,19,20.2,5.6358,3.0502 82 | Perch,85,17.8,19.6,20.8,5.1376,3.0368 83 | Perch,85,18.2,20,21,5.082,2.772 84 | Perch,110,19,21,22.5,5.6925,3.555 85 | Perch,115,19,21,22.5,5.9175,3.3075 86 | Perch,125,19,21,22.5,5.6925,3.6675 87 | Perch,130,19.3,21.3,22.8,6.384,3.534 88 | Perch,120,20,22,23.5,6.11,3.4075 89 | Perch,120,20,22,23.5,5.64,3.525 90 | Perch,130,20,22,23.5,6.11,3.525 91 | Perch,135,20,22,23.5,5.875,3.525 92 | Perch,110,20,22,23.5,5.5225,3.995 93 | Perch,130,20.5,22.5,24,5.856,3.624 94 | Perch,150,20.5,22.5,24,6.792,3.624 95 | Perch,145,20.7,22.7,24.2,5.9532,3.63 96 | Perch,150,21,23,24.5,5.2185,3.626 97 | Perch,170,21.5,23.5,25,6.275,3.725 98 | Perch,225,22,24,25.5,7.293,3.723 99 | Perch,145,22,24,25.5,6.375,3.825 100 | Perch,188,22.6,24.6,26.2,6.7334,4.1658 101 | Perch,180,23,25,26.5,6.4395,3.6835 102 | Perch,197,23.5,25.6,27,6.561,4.239 103 | Perch,218,25,26.5,28,7.168,4.144 104 | Perch,300,25.2,27.3,28.7,8.323,5.1373 105 | Perch,260,25.4,27.5,28.9,7.1672,4.335 106 | Perch,265,25.4,27.5,28.9,7.0516,4.335 107 | Perch,250,25.4,27.5,28.9,7.2828,4.5662 108 | Perch,250,25.9,28,29.4,7.8204,4.2042 109 | Perch,300,26.9,28.7,30.1,7.5852,4.6354 110 | Perch,320,27.8,30,31.6,7.6156,4.7716 111 | Perch,514,30.5,32.8,34,10.03,6.018 112 | Perch,556,32,34.5,36.5,10.2565,6.3875 113 | Perch,840,32.5,35,37.3,11.4884,7.7957 114 | Perch,685,34,36.5,39,10.881,6.864 115 | Perch,700,34,36,38.3,10.6091,6.7408 116 | Perch,700,34.5,37,39.4,10.835,6.2646 117 | Perch,690,34.6,37,39.3,10.5717,6.3666 118 | Perch,900,36.5,39,41.4,11.1366,7.4934 119 | Perch,650,36.5,39,41.4,11.1366,6.003 120 | Perch,820,36.6,39,41.3,12.4313,7.3514 121 | Perch,850,36.9,40,42.3,11.9286,7.1064 122 | Perch,900,37,40,42.5,11.73,7.225 123 | Perch,1015,37,40,42.4,12.3808,7.4624 124 | Perch,820,37.1,40,42.5,11.135,6.63 125 | Perch,1100,39,42,44.6,12.8002,6.8684 126 | Perch,1000,39.8,43,45.2,11.9328,7.2772 127 | Perch,1100,40.1,43,45.5,12.5125,7.4165 128 | Perch,1000,40.2,43.5,46,12.604,8.142 129 | Perch,1000,41.1,44,46.6,12.4888,7.5958 130 | Pike,200,30,32.3,34.8,5.568,3.3756 131 | Pike,300,31.7,34,37.8,5.7078,4.158 132 | Pike,300,32.7,35,38.8,5.9364,4.3844 133 | Pike,300,34.8,37.3,39.8,6.2884,4.0198 134 | Pike,430,35.5,38,40.5,7.29,4.5765 135 | Pike,345,36,38.5,41,6.396,3.977 136 | Pike,456,40,42.5,45.5,7.28,4.3225 137 | Pike,510,40,42.5,45.5,6.825,4.459 138 | Pike,540,40.1,43,45.8,7.786,5.1296 139 | Pike,500,42,45,48,6.96,4.896 140 | Pike,567,43.2,46,48.7,7.792,4.87 141 | Pike,770,44.8,48,51.2,7.68,5.376 142 | Pike,950,48.3,51.7,55.1,8.9262,6.1712 143 | Pike,1250,52,56,59.7,10.6863,6.9849 144 | Pike,1600,56,60,64,9.6,6.144 145 | Pike,1550,56,60,64,9.6,6.144 146 | Pike,1650,59,63.4,68,10.812,7.48 147 | Smelt,6.7,9.3,9.8,10.8,1.7388,1.0476 148 | Smelt,7.5,10,10.5,11.6,1.972,1.16 149 | Smelt,7,10.1,10.6,11.6,1.7284,1.1484 150 | Smelt,9.7,10.4,11,12,2.196,1.38 151 | Smelt,9.8,10.7,11.2,12.4,2.0832,1.2772 152 | Smelt,8.7,10.8,11.3,12.6,1.9782,1.2852 153 | Smelt,10,11.3,11.8,13.1,2.2139,1.2838 154 | Smelt,9.9,11.3,11.8,13.1,2.2139,1.1659 155 | Smelt,9.8,11.4,12,13.2,2.2044,1.1484 156 | Smelt,12.2,11.5,12.2,13.4,2.0904,1.3936 157 | Smelt,13.4,11.7,12.4,13.5,2.43,1.269 158 | Smelt,12.2,12.1,13,13.8,2.277,1.2558 159 | Smelt,19.7,13.2,14.3,15.2,2.8728,2.0672 160 | Smelt,19.9,13.8,15,16.2,2.9322,1.8792 161 | -------------------------------------------------------------------------------- /datasets/Fish_processed.csv: -------------------------------------------------------------------------------- 1 | Weight,Length1,Length2,Length3,Height,Width,Species_Parkki,Species_Perch,Species_Pike,Species_Roach,Species_Smelt,Species_Whitefish 2 | 242.0,23.2,25.4,30.0,11.52,4.02,0,0,0,0,0,0 3 | 290.0,24.0,26.3,31.2,12.48,4.3056,0,0,0,0,0,0 4 | 340.0,23.9,26.5,31.1,12.3778,4.6961,0,0,0,0,0,0 5 | 363.0,26.3,29.0,33.5,12.73,4.4555,0,0,0,0,0,0 6 | 430.0,26.5,29.0,34.0,12.444,5.134,0,0,0,0,0,0 7 | 450.0,26.8,29.7,34.7,13.6024,4.9274,0,0,0,0,0,0 8 | 500.0,26.8,29.7,34.5,14.1795,5.2785,0,0,0,0,0,0 9 | 390.0,27.6,30.0,35.0,12.67,4.69,0,0,0,0,0,0 10 | 450.0,27.6,30.0,35.1,14.0049,4.8438,0,0,0,0,0,0 11 | 500.0,28.5,30.7,36.2,14.2266,4.9594,0,0,0,0,0,0 12 | 475.0,28.4,31.0,36.2,14.2628,5.1042,0,0,0,0,0,0 13 | 500.0,28.7,31.0,36.2,14.3714,4.8146,0,0,0,0,0,0 14 | 500.0,29.1,31.5,36.4,13.7592,4.368,0,0,0,0,0,0 15 | 340.0,29.5,32.0,37.3,13.9129,5.0728,0,0,0,0,0,0 16 | 600.0,29.4,32.0,37.2,14.9544,5.1708,0,0,0,0,0,0 17 | 600.0,29.4,32.0,37.2,15.438,5.58,0,0,0,0,0,0 18 | 700.0,30.4,33.0,38.3,14.8604,5.2854,0,0,0,0,0,0 19 | 700.0,30.4,33.0,38.5,14.938,5.1975,0,0,0,0,0,0 20 | 610.0,30.9,33.5,38.6,15.633,5.1338,0,0,0,0,0,0 21 | 650.0,31.0,33.5,38.7,14.4738,5.7276,0,0,0,0,0,0 22 | 575.0,31.3,34.0,39.5,15.1285,5.5695,0,0,0,0,0,0 23 | 685.0,31.4,34.0,39.2,15.9936,5.3704,0,0,0,0,0,0 24 | 620.0,31.5,34.5,39.7,15.5227,5.2801,0,0,0,0,0,0 25 | 680.0,31.8,35.0,40.6,15.4686,6.1306,0,0,0,0,0,0 26 | 700.0,31.9,35.0,40.5,16.2405,5.589,0,0,0,0,0,0 27 | 725.0,31.8,35.0,40.9,16.36,6.0532,0,0,0,0,0,0 28 | 720.0,32.0,35.0,40.6,16.3618,6.09,0,0,0,0,0,0 29 | 714.0,32.7,36.0,41.5,16.517,5.8515,0,0,0,0,0,0 30 | 850.0,32.8,36.0,41.6,16.8896,6.1984,0,0,0,0,0,0 31 | 1000.0,33.5,37.0,42.6,18.957,6.603,0,0,0,0,0,0 32 | 920.0,35.0,38.5,44.1,18.0369,6.3063,0,0,0,0,0,0 33 | 955.0,35.0,38.5,44.0,18.084,6.292,0,0,0,0,0,0 34 | 925.0,36.2,39.5,45.3,18.7542,6.7497,0,0,0,0,0,0 35 | 975.0,37.4,41.0,45.9,18.6354,6.7473,0,0,0,0,0,0 36 | 950.0,38.0,41.0,46.5,17.6235,6.3705,0,0,0,0,0,0 37 | 40.0,12.9,14.1,16.2,4.1472,2.268,0,0,0,1,0,0 38 | 69.0,16.5,18.2,20.3,5.2983,2.8217,0,0,0,1,0,0 39 | 78.0,17.5,18.8,21.2,5.5756,2.9044,0,0,0,1,0,0 40 | 87.0,18.2,19.8,22.2,5.6166,3.1746,0,0,0,1,0,0 41 | 120.0,18.6,20.0,22.2,6.216,3.5742,0,0,0,1,0,0 42 | 0.0,19.0,20.5,22.8,6.4752,3.3516,0,0,0,1,0,0 43 | 110.0,19.1,20.8,23.1,6.1677,3.3957,0,0,0,1,0,0 44 | 120.0,19.4,21.0,23.7,6.1146,3.2943,0,0,0,1,0,0 45 | 150.0,20.4,22.0,24.7,5.8045,3.7544,0,0,0,1,0,0 46 | 145.0,20.5,22.0,24.3,6.6339,3.5478,0,0,0,1,0,0 47 | 160.0,20.5,22.5,25.3,7.0334,3.8203,0,0,0,1,0,0 48 | 140.0,21.0,22.5,25.0,6.55,3.325,0,0,0,1,0,0 49 | 160.0,21.1,22.5,25.0,6.4,3.8,0,0,0,1,0,0 50 | 169.0,22.0,24.0,27.2,7.5344,3.8352,0,0,0,1,0,0 51 | 161.0,22.0,23.4,26.7,6.9153,3.6312,0,0,0,1,0,0 52 | 200.0,22.1,23.5,26.8,7.3968,4.1272,0,0,0,1,0,0 53 | 180.0,23.6,25.2,27.9,7.0866,3.906,0,0,0,1,0,0 54 | 290.0,24.0,26.0,29.2,8.8768,4.4968,0,0,0,1,0,0 55 | 272.0,25.0,27.0,30.6,8.568,4.7736,0,0,0,1,0,0 56 | 390.0,29.5,31.7,35.0,9.485,5.355,0,0,0,1,0,0 57 | 270.0,23.6,26.0,28.7,8.3804,4.2476,0,0,0,0,0,1 58 | 270.0,24.1,26.5,29.3,8.1454,4.2485,0,0,0,0,0,1 59 | 306.0,25.6,28.0,30.8,8.778,4.6816,0,0,0,0,0,1 60 | 540.0,28.5,31.0,34.0,10.744,6.562,0,0,0,0,0,1 61 | 800.0,33.7,36.4,39.6,11.7612,6.5736,0,0,0,0,0,1 62 | 1000.0,37.3,40.0,43.5,12.354,6.525,0,0,0,0,0,1 63 | 55.0,13.5,14.7,16.5,6.8475,2.3265,1,0,0,0,0,0 64 | 60.0,14.3,15.5,17.4,6.5772,2.3142,1,0,0,0,0,0 65 | 90.0,16.3,17.7,19.8,7.4052,2.673,1,0,0,0,0,0 66 | 120.0,17.5,19.0,21.3,8.3922,2.9181,1,0,0,0,0,0 67 | 150.0,18.4,20.0,22.4,8.8928,3.2928,1,0,0,0,0,0 68 | 140.0,19.0,20.7,23.2,8.5376,3.2944,1,0,0,0,0,0 69 | 170.0,19.0,20.7,23.2,9.396,3.4104,1,0,0,0,0,0 70 | 145.0,19.8,21.5,24.1,9.7364,3.1571,1,0,0,0,0,0 71 | 200.0,21.2,23.0,25.8,10.3458,3.6636,1,0,0,0,0,0 72 | 273.0,23.0,25.0,28.0,11.088,4.144,1,0,0,0,0,0 73 | 300.0,24.0,26.0,29.0,11.368,4.234,1,0,0,0,0,0 74 | 5.9,7.5,8.4,8.8,2.112,1.408,0,1,0,0,0,0 75 | 32.0,12.5,13.7,14.7,3.528,1.9992,0,1,0,0,0,0 76 | 40.0,13.8,15.0,16.0,3.824,2.432,0,1,0,0,0,0 77 | 51.5,15.0,16.2,17.2,4.5924,2.6316,0,1,0,0,0,0 78 | 70.0,15.7,17.4,18.5,4.588,2.9415,0,1,0,0,0,0 79 | 100.0,16.2,18.0,19.2,5.2224,3.3216,0,1,0,0,0,0 80 | 78.0,16.8,18.7,19.4,5.1992,3.1234,0,1,0,0,0,0 81 | 80.0,17.2,19.0,20.2,5.6358,3.0502,0,1,0,0,0,0 82 | 85.0,17.8,19.6,20.8,5.1376,3.0368,0,1,0,0,0,0 83 | 85.0,18.2,20.0,21.0,5.082,2.772,0,1,0,0,0,0 84 | 110.0,19.0,21.0,22.5,5.6925,3.555,0,1,0,0,0,0 85 | 115.0,19.0,21.0,22.5,5.9175,3.3075,0,1,0,0,0,0 86 | 125.0,19.0,21.0,22.5,5.6925,3.6675,0,1,0,0,0,0 87 | 130.0,19.3,21.3,22.8,6.384,3.534,0,1,0,0,0,0 88 | 120.0,20.0,22.0,23.5,6.11,3.4075,0,1,0,0,0,0 89 | 120.0,20.0,22.0,23.5,5.64,3.525,0,1,0,0,0,0 90 | 130.0,20.0,22.0,23.5,6.11,3.525,0,1,0,0,0,0 91 | 135.0,20.0,22.0,23.5,5.875,3.525,0,1,0,0,0,0 92 | 110.0,20.0,22.0,23.5,5.5225,3.995,0,1,0,0,0,0 93 | 130.0,20.5,22.5,24.0,5.856,3.624,0,1,0,0,0,0 94 | 150.0,20.5,22.5,24.0,6.792,3.624,0,1,0,0,0,0 95 | 145.0,20.7,22.7,24.2,5.9532,3.63,0,1,0,0,0,0 96 | 150.0,21.0,23.0,24.5,5.2185,3.626,0,1,0,0,0,0 97 | 170.0,21.5,23.5,25.0,6.275,3.725,0,1,0,0,0,0 98 | 225.0,22.0,24.0,25.5,7.293,3.723,0,1,0,0,0,0 99 | 145.0,22.0,24.0,25.5,6.375,3.825,0,1,0,0,0,0 100 | 188.0,22.6,24.6,26.2,6.7334,4.1658,0,1,0,0,0,0 101 | 180.0,23.0,25.0,26.5,6.4395,3.6835,0,1,0,0,0,0 102 | 197.0,23.5,25.6,27.0,6.561,4.239,0,1,0,0,0,0 103 | 218.0,25.0,26.5,28.0,7.168,4.144,0,1,0,0,0,0 104 | 300.0,25.2,27.3,28.7,8.323,5.1373,0,1,0,0,0,0 105 | 260.0,25.4,27.5,28.9,7.1672,4.335,0,1,0,0,0,0 106 | 265.0,25.4,27.5,28.9,7.0516,4.335,0,1,0,0,0,0 107 | 250.0,25.4,27.5,28.9,7.2828,4.5662,0,1,0,0,0,0 108 | 250.0,25.9,28.0,29.4,7.8204,4.2042,0,1,0,0,0,0 109 | 300.0,26.9,28.7,30.1,7.5852,4.6354,0,1,0,0,0,0 110 | 320.0,27.8,30.0,31.6,7.6156,4.7716,0,1,0,0,0,0 111 | 514.0,30.5,32.8,34.0,10.03,6.018,0,1,0,0,0,0 112 | 556.0,32.0,34.5,36.5,10.2565,6.3875,0,1,0,0,0,0 113 | 840.0,32.5,35.0,37.3,11.4884,7.7957,0,1,0,0,0,0 114 | 685.0,34.0,36.5,39.0,10.881,6.864,0,1,0,0,0,0 115 | 700.0,34.0,36.0,38.3,10.6091,6.7408,0,1,0,0,0,0 116 | 700.0,34.5,37.0,39.4,10.835,6.2646,0,1,0,0,0,0 117 | 690.0,34.6,37.0,39.3,10.5717,6.3666,0,1,0,0,0,0 118 | 900.0,36.5,39.0,41.4,11.1366,7.4934,0,1,0,0,0,0 119 | 650.0,36.5,39.0,41.4,11.1366,6.003,0,1,0,0,0,0 120 | 820.0,36.6,39.0,41.3,12.4313,7.3514,0,1,0,0,0,0 121 | 850.0,36.9,40.0,42.3,11.9286,7.1064,0,1,0,0,0,0 122 | 900.0,37.0,40.0,42.5,11.73,7.225,0,1,0,0,0,0 123 | 1015.0,37.0,40.0,42.4,12.3808,7.4624,0,1,0,0,0,0 124 | 820.0,37.1,40.0,42.5,11.135,6.63,0,1,0,0,0,0 125 | 1100.0,39.0,42.0,44.6,12.8002,6.8684,0,1,0,0,0,0 126 | 1000.0,39.8,43.0,45.2,11.9328,7.2772,0,1,0,0,0,0 127 | 1100.0,40.1,43.0,45.5,12.5125,7.4165,0,1,0,0,0,0 128 | 1000.0,40.2,43.5,46.0,12.604,8.142,0,1,0,0,0,0 129 | 1000.0,41.1,44.0,46.6,12.4888,7.5958,0,1,0,0,0,0 130 | 200.0,30.0,32.3,34.8,5.568,3.3756,0,0,1,0,0,0 131 | 300.0,31.7,34.0,37.8,5.7078,4.158,0,0,1,0,0,0 132 | 300.0,32.7,35.0,38.8,5.9364,4.3844,0,0,1,0,0,0 133 | 300.0,34.8,37.3,39.8,6.2884,4.0198,0,0,1,0,0,0 134 | 430.0,35.5,38.0,40.5,7.29,4.5765,0,0,1,0,0,0 135 | 345.0,36.0,38.5,41.0,6.396,3.977,0,0,1,0,0,0 136 | 456.0,40.0,42.5,45.5,7.28,4.3225,0,0,1,0,0,0 137 | 510.0,40.0,42.5,45.5,6.825,4.459,0,0,1,0,0,0 138 | 540.0,40.1,43.0,45.8,7.786,5.1296,0,0,1,0,0,0 139 | 500.0,42.0,45.0,48.0,6.96,4.896,0,0,1,0,0,0 140 | 567.0,43.2,46.0,48.7,7.792,4.87,0,0,1,0,0,0 141 | 770.0,44.8,48.0,51.2,7.68,5.376,0,0,1,0,0,0 142 | 950.0,48.3,51.7,55.1,8.9262,6.1712,0,0,1,0,0,0 143 | 1250.0,52.0,56.0,59.7,10.6863,6.9849,0,0,1,0,0,0 144 | 1600.0,56.0,60.0,64.0,9.6,6.144,0,0,1,0,0,0 145 | 1550.0,56.0,60.0,64.0,9.6,6.144,0,0,1,0,0,0 146 | 1650.0,59.0,63.4,68.0,10.812,7.48,0,0,1,0,0,0 147 | 6.7,9.3,9.8,10.8,1.7388,1.0476,0,0,0,0,1,0 148 | 7.5,10.0,10.5,11.6,1.972,1.16,0,0,0,0,1,0 149 | 7.0,10.1,10.6,11.6,1.7284,1.1484,0,0,0,0,1,0 150 | 9.7,10.4,11.0,12.0,2.196,1.38,0,0,0,0,1,0 151 | 9.8,10.7,11.2,12.4,2.0832,1.2772,0,0,0,0,1,0 152 | 8.7,10.8,11.3,12.6,1.9782,1.2852,0,0,0,0,1,0 153 | 10.0,11.3,11.8,13.1,2.2139,1.2838,0,0,0,0,1,0 154 | 9.9,11.3,11.8,13.1,2.2139,1.1659,0,0,0,0,1,0 155 | 9.8,11.4,12.0,13.2,2.2044,1.1484,0,0,0,0,1,0 156 | 12.2,11.5,12.2,13.4,2.0904,1.3936,0,0,0,0,1,0 157 | 13.4,11.7,12.4,13.5,2.43,1.269,0,0,0,0,1,0 158 | 12.2,12.1,13.0,13.8,2.277,1.2558,0,0,0,0,1,0 159 | 19.7,13.2,14.3,15.2,2.8728,2.0672,0,0,0,0,1,0 160 | 19.9,13.8,15.0,16.2,2.9322,1.8792,0,0,0,0,1,0 161 | -------------------------------------------------------------------------------- /datasets/Credit.csv: -------------------------------------------------------------------------------- 1 | Income,Limit,Rating,Cards,Age,Education,Own,Student,Married,Region,Balance 2 | 14.891,3606,283,2,34,11,No,No,Yes,South,333 3 | 106.025,6645,483,3,82,15,Yes,Yes,Yes,West,903 4 | 104.593,7075,514,4,71,11,No,No,No,West,580 5 | 148.924,9504,681,3,36,11,Yes,No,No,West,964 6 | 55.882,4897,357,2,68,16,No,No,Yes,South,331 7 | 80.18,8047,569,4,77,10,No,No,No,South,1151 8 | 20.996,3388,259,2,37,12,Yes,No,No,East,203 9 | 71.408,7114,512,2,87,9,No,No,No,West,872 10 | 15.125,3300,266,5,66,13,Yes,No,No,South,279 11 | 71.061,6819,491,3,41,19,Yes,Yes,Yes,East,1350 12 | 63.095,8117,589,4,30,14,No,No,Yes,South,1407 13 | 15.045,1311,138,3,64,16,No,No,No,South,0 14 | 80.616,5308,394,1,57,7,Yes,No,Yes,West,204 15 | 43.682,6922,511,1,49,9,No,No,Yes,South,1081 16 | 19.144,3291,269,2,75,13,Yes,No,No,East,148 17 | 20.089,2525,200,3,57,15,Yes,No,Yes,East,0 18 | 53.598,3714,286,3,73,17,Yes,No,Yes,East,0 19 | 36.496,4378,339,3,69,15,Yes,No,Yes,West,368 20 | 49.57,6384,448,1,28,9,Yes,No,Yes,West,891 21 | 42.079,6626,479,2,44,9,No,No,No,West,1048 22 | 17.7,2860,235,4,63,16,Yes,No,No,West,89 23 | 37.348,6378,458,1,72,17,Yes,No,No,South,968 24 | 20.103,2631,213,3,61,10,No,No,Yes,East,0 25 | 64.027,5179,398,5,48,8,No,No,Yes,East,411 26 | 10.742,1757,156,3,57,15,Yes,No,No,South,0 27 | 14.09,4323,326,5,25,16,Yes,No,Yes,East,671 28 | 42.471,3625,289,6,44,12,Yes,Yes,No,South,654 29 | 32.793,4534,333,2,44,16,No,No,No,East,467 30 | 186.634,13414,949,2,41,14,Yes,No,Yes,East,1809 31 | 26.813,5611,411,4,55,16,Yes,No,No,South,915 32 | 34.142,5666,413,4,47,5,Yes,No,Yes,South,863 33 | 28.941,2733,210,5,43,16,No,No,Yes,West,0 34 | 134.181,7838,563,2,48,13,Yes,No,No,South,526 35 | 31.367,1829,162,4,30,10,No,No,Yes,South,0 36 | 20.15,2646,199,2,25,14,Yes,No,Yes,West,0 37 | 23.35,2558,220,3,49,12,Yes,Yes,No,South,419 38 | 62.413,6457,455,2,71,11,Yes,No,Yes,South,762 39 | 30.007,6481,462,2,69,9,Yes,No,Yes,South,1093 40 | 11.795,3899,300,4,25,10,Yes,No,No,South,531 41 | 13.647,3461,264,4,47,14,No,No,Yes,South,344 42 | 34.95,3327,253,3,54,14,Yes,No,No,East,50 43 | 113.659,7659,538,2,66,15,No,Yes,Yes,East,1155 44 | 44.158,4763,351,2,66,13,Yes,No,Yes,West,385 45 | 36.929,6257,445,1,24,14,Yes,No,Yes,West,976 46 | 31.861,6375,469,3,25,16,Yes,No,Yes,South,1120 47 | 77.38,7569,564,3,50,12,Yes,No,Yes,South,997 48 | 19.531,5043,376,2,64,16,Yes,Yes,Yes,West,1241 49 | 44.646,4431,320,2,49,15,No,Yes,Yes,South,797 50 | 44.522,2252,205,6,72,15,No,No,Yes,West,0 51 | 43.479,4569,354,4,49,13,No,Yes,Yes,East,902 52 | 36.362,5183,376,3,49,15,No,No,Yes,East,654 53 | 39.705,3969,301,2,27,20,No,No,Yes,East,211 54 | 44.205,5441,394,1,32,12,No,No,Yes,South,607 55 | 16.304,5466,413,4,66,10,No,No,Yes,West,957 56 | 15.333,1499,138,2,47,9,Yes,No,Yes,West,0 57 | 32.916,1786,154,2,60,8,Yes,No,Yes,West,0 58 | 57.1,4742,372,7,79,18,Yes,No,Yes,West,379 59 | 76.273,4779,367,4,65,14,Yes,No,Yes,South,133 60 | 10.354,3480,281,2,70,17,No,No,Yes,South,333 61 | 51.872,5294,390,4,81,17,Yes,No,No,South,531 62 | 35.51,5198,364,2,35,20,Yes,No,No,West,631 63 | 21.238,3089,254,3,59,10,Yes,No,No,South,108 64 | 30.682,1671,160,2,77,7,Yes,No,No,South,0 65 | 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49.927,6396,485,3,75,17,Yes,No,Yes,South,890 286 | 14.711,2047,167,2,67,6,No,No,Yes,South,0 287 | 18.967,1626,156,2,41,11,Yes,No,Yes,West,0 288 | 18.036,1552,142,2,48,15,Yes,No,No,South,0 289 | 60.449,3098,272,4,69,8,No,No,Yes,South,0 290 | 16.711,5274,387,3,42,16,Yes,No,Yes,West,863 291 | 10.852,3907,296,2,30,9,No,No,No,South,485 292 | 26.37,3235,268,5,78,11,No,No,Yes,West,159 293 | 24.088,3665,287,4,56,13,Yes,No,Yes,South,309 294 | 51.532,5096,380,2,31,15,No,No,Yes,South,481 295 | 140.672,11200,817,7,46,9,No,No,Yes,East,1677 296 | 42.915,2532,205,4,42,13,No,No,Yes,West,0 297 | 27.272,1389,149,5,67,10,Yes,No,Yes,South,0 298 | 65.896,5140,370,1,49,17,Yes,No,Yes,South,293 299 | 55.054,4381,321,3,74,17,No,No,Yes,West,188 300 | 20.791,2672,204,1,70,18,Yes,No,No,East,0 301 | 24.919,5051,372,3,76,11,Yes,No,Yes,East,711 302 | 21.786,4632,355,1,50,17,No,No,Yes,South,580 303 | 31.335,3526,289,3,38,7,Yes,No,No,South,172 304 | 59.855,4964,365,1,46,13,Yes,No,Yes,South,295 305 | 44.061,4970,352,1,79,11,No,No,Yes,East,414 306 | 82.706,7506,536,2,64,13,Yes,No,Yes,West,905 307 | 24.46,1924,165,2,50,14,Yes,No,Yes,West,0 308 | 45.12,3762,287,3,80,8,No,No,Yes,South,70 309 | 75.406,3874,298,3,41,14,Yes,No,Yes,West,0 310 | 14.956,4640,332,2,33,6,No,No,No,West,681 311 | 75.257,7010,494,3,34,18,Yes,No,Yes,South,885 312 | 33.694,4891,369,1,52,16,No,Yes,No,East,1036 313 | 23.375,5429,396,3,57,15,Yes,No,Yes,South,844 314 | 27.825,5227,386,6,63,11,No,No,Yes,South,823 315 | 92.386,7685,534,2,75,18,Yes,No,Yes,West,843 316 | 115.52,9272,656,2,69,14,No,No,No,East,1140 317 | 14.479,3907,296,3,43,16,No,No,Yes,South,463 318 | 52.179,7306,522,2,57,14,No,No,No,West,1142 319 | 68.462,4712,340,2,71,16,No,No,Yes,South,136 320 | 18.951,1485,129,3,82,13,Yes,No,No,South,0 321 | 27.59,2586,229,5,54,16,No,No,Yes,East,0 322 | 16.279,1160,126,3,78,13,No,Yes,Yes,East,5 323 | 25.078,3096,236,2,27,15,Yes,No,Yes,South,81 324 | 27.229,3484,282,6,51,11,No,No,No,South,265 325 | 182.728,13913,982,4,98,17,No,No,Yes,South,1999 326 | 31.029,2863,223,2,66,17,No,Yes,Yes,West,415 327 | 17.765,5072,364,1,66,12,Yes,No,Yes,South,732 328 | 125.48,10230,721,3,82,16,No,No,Yes,South,1361 329 | 49.166,6662,508,3,68,14,Yes,No,No,West,984 330 | 41.192,3673,297,3,54,16,Yes,No,Yes,South,121 331 | 94.193,7576,527,2,44,16,Yes,No,Yes,South,846 332 | 20.405,4543,329,2,72,17,No,Yes,No,West,1054 333 | 12.581,3976,291,2,48,16,No,No,Yes,South,474 334 | 62.328,5228,377,3,83,15,No,No,No,South,380 335 | 21.011,3402,261,2,68,17,No,No,Yes,East,182 336 | 24.23,4756,351,2,64,15,Yes,No,Yes,South,594 337 | 24.314,3409,270,2,23,7,Yes,No,Yes,South,194 338 | 32.856,5884,438,4,68,13,No,No,No,South,926 339 | 12.414,855,119,3,32,12,No,No,Yes,East,0 340 | 41.365,5303,377,1,45,14,No,No,No,South,606 341 | 149.316,10278,707,1,80,16,No,No,No,East,1107 342 | 27.794,3807,301,4,35,8,Yes,No,Yes,East,320 343 | 13.234,3922,299,2,77,17,Yes,No,Yes,South,426 344 | 14.595,2955,260,5,37,9,No,No,Yes,East,204 345 | 10.735,3746,280,2,44,17,Yes,No,Yes,South,410 346 | 48.218,5199,401,7,39,10,No,No,Yes,West,633 347 | 30.012,1511,137,2,33,17,No,No,Yes,South,0 348 | 21.551,5380,420,5,51,18,No,No,Yes,West,907 349 | 160.231,10748,754,2,69,17,No,No,No,South,1192 350 | 13.433,1134,112,3,70,14,No,No,Yes,South,0 351 | 48.577,5145,389,3,71,13,Yes,No,Yes,West,503 352 | 30.002,1561,155,4,70,13,Yes,No,Yes,South,0 353 | 61.62,5140,374,1,71,9,No,No,Yes,South,302 354 | 104.483,7140,507,2,41,14,No,No,Yes,East,583 355 | 41.868,4716,342,2,47,18,No,No,No,South,425 356 | 12.068,3873,292,1,44,18,Yes,No,Yes,West,413 357 | 180.682,11966,832,2,58,8,Yes,No,Yes,East,1405 358 | 34.48,6090,442,3,36,14,No,No,No,South,962 359 | 39.609,2539,188,1,40,14,No,No,Yes,West,0 360 | 30.111,4336,339,1,81,18,No,No,Yes,South,347 361 | 12.335,4471,344,3,79,12,No,No,Yes,East,611 362 | 53.566,5891,434,4,82,10,Yes,No,No,South,712 363 | 53.217,4943,362,2,46,16,Yes,No,Yes,West,382 364 | 26.162,5101,382,3,62,19,Yes,No,No,East,710 365 | 64.173,6127,433,1,80,10,No,No,Yes,South,578 366 | 128.669,9824,685,3,67,16,No,No,Yes,West,1243 367 | 113.772,6442,489,4,69,15,No,Yes,Yes,South,790 368 | 61.069,7871,564,3,56,14,No,No,Yes,South,1264 369 | 23.793,3615,263,2,70,14,No,No,No,East,216 370 | 89,5759,440,3,37,6,Yes,No,No,South,345 371 | 71.682,8028,599,3,57,16,No,No,Yes,South,1208 372 | 35.61,6135,466,4,40,12,No,No,No,South,992 373 | 39.116,2150,173,4,75,15,No,No,No,South,0 374 | 19.782,3782,293,2,46,16,Yes,Yes,No,South,840 375 | 55.412,5354,383,2,37,16,Yes,Yes,Yes,South,1003 376 | 29.4,4840,368,3,76,18,Yes,No,Yes,South,588 377 | 20.974,5673,413,5,44,16,Yes,No,Yes,South,1000 378 | 87.625,7167,515,2,46,10,Yes,No,No,East,767 379 | 28.144,1567,142,3,51,10,No,No,Yes,South,0 380 | 19.349,4941,366,1,33,19,No,No,Yes,South,717 381 | 53.308,2860,214,1,84,10,No,No,Yes,South,0 382 | 115.123,7760,538,3,83,14,Yes,No,No,East,661 383 | 101.788,8029,574,2,84,11,No,No,Yes,South,849 384 | 24.824,5495,409,1,33,9,No,Yes,No,South,1352 385 | 14.292,3274,282,9,64,9,No,No,Yes,South,382 386 | 20.088,1870,180,3,76,16,No,No,No,East,0 387 | 26.4,5640,398,3,58,15,Yes,No,No,West,905 388 | 19.253,3683,287,4,57,10,No,No,No,East,371 389 | 16.529,1357,126,3,62,9,No,No,No,West,0 390 | 37.878,6827,482,2,80,13,Yes,No,No,South,1129 391 | 83.948,7100,503,2,44,18,No,No,No,South,806 392 | 135.118,10578,747,3,81,15,Yes,No,Yes,West,1393 393 | 73.327,6555,472,2,43,15,Yes,No,No,South,721 394 | 25.974,2308,196,2,24,10,No,No,No,West,0 395 | 17.316,1335,138,2,65,13,No,No,No,East,0 396 | 49.794,5758,410,4,40,8,No,No,No,South,734 397 | 12.096,4100,307,3,32,13,No,No,Yes,South,560 398 | 13.364,3838,296,5,65,17,No,No,No,East,480 399 | 57.872,4171,321,5,67,12,Yes,No,Yes,South,138 400 | 37.728,2525,192,1,44,13,No,No,Yes,South,0 401 | 18.701,5524,415,5,64,7,Yes,No,No,West,966 402 | -------------------------------------------------------------------------------- /datasets/Auto.csv: -------------------------------------------------------------------------------- 1 | mpg,cylinders,displacement,horsepower,weight,acceleration,year,origin,name 2 | 18,8,307,130,3504,12,70,1,chevrolet chevelle malibu 3 | 15,8,350,165,3693,11.5,70,1,buick skylark 320 4 | 18,8,318,150,3436,11,70,1,plymouth satellite 5 | 16,8,304,150,3433,12,70,1,amc rebel sst 6 | 17,8,302,140,3449,10.5,70,1,ford torino 7 | 15,8,429,198,4341,10,70,1,ford galaxie 500 8 | 14,8,454,220,4354,9,70,1,chevrolet impala 9 | 14,8,440,215,4312,8.5,70,1,plymouth fury iii 10 | 14,8,455,225,4425,10,70,1,pontiac catalina 11 | 15,8,390,190,3850,8.5,70,1,amc ambassador dpl 12 | 15,8,383,170,3563,10,70,1,dodge challenger se 13 | 14,8,340,160,3609,8,70,1,plymouth 'cuda 340 14 | 15,8,400,150,3761,9.5,70,1,chevrolet monte carlo 15 | 14,8,455,225,3086,10,70,1,buick estate wagon (sw) 16 | 24,4,113,95,2372,15,70,3,toyota corona mark ii 17 | 22,6,198,95,2833,15.5,70,1,plymouth duster 18 | 18,6,199,97,2774,15.5,70,1,amc hornet 19 | 21,6,200,85,2587,16,70,1,ford maverick 20 | 27,4,97,88,2130,14.5,70,3,datsun pl510 21 | 26,4,97,46,1835,20.5,70,2,volkswagen 1131 deluxe sedan 22 | 25,4,110,87,2672,17.5,70,2,peugeot 504 23 | 24,4,107,90,2430,14.5,70,2,audi 100 ls 24 | 25,4,104,95,2375,17.5,70,2,saab 99e 25 | 26,4,121,113,2234,12.5,70,2,bmw 2002 26 | 21,6,199,90,2648,15,70,1,amc gremlin 27 | 10,8,360,215,4615,14,70,1,ford f250 28 | 10,8,307,200,4376,15,70,1,chevy c20 29 | 11,8,318,210,4382,13.5,70,1,dodge d200 30 | 9,8,304,193,4732,18.5,70,1,hi 1200d 31 | 27,4,97,88,2130,14.5,71,3,datsun pl510 32 | 28,4,140,90,2264,15.5,71,1,chevrolet vega 2300 33 | 25,4,113,95,2228,14,71,3,toyota corona 34 | 25,4,98,?,2046,19,71,1,ford pinto 35 | 19,6,232,100,2634,13,71,1,amc gremlin 36 | 16,6,225,105,3439,15.5,71,1,plymouth satellite custom 37 | 17,6,250,100,3329,15.5,71,1,chevrolet chevelle malibu 38 | 19,6,250,88,3302,15.5,71,1,ford torino 500 39 | 18,6,232,100,3288,15.5,71,1,amc matador 40 | 14,8,350,165,4209,12,71,1,chevrolet impala 41 | 14,8,400,175,4464,11.5,71,1,pontiac catalina brougham 42 | 14,8,351,153,4154,13.5,71,1,ford galaxie 500 43 | 14,8,318,150,4096,13,71,1,plymouth fury iii 44 | 12,8,383,180,4955,11.5,71,1,dodge monaco (sw) 45 | 13,8,400,170,4746,12,71,1,ford country squire (sw) 46 | 13,8,400,175,5140,12,71,1,pontiac safari (sw) 47 | 18,6,258,110,2962,13.5,71,1,amc hornet sportabout (sw) 48 | 22,4,140,72,2408,19,71,1,chevrolet vega (sw) 49 | 19,6,250,100,3282,15,71,1,pontiac firebird 50 | 18,6,250,88,3139,14.5,71,1,ford mustang 51 | 23,4,122,86,2220,14,71,1,mercury capri 2000 52 | 28,4,116,90,2123,14,71,2,opel 1900 53 | 30,4,79,70,2074,19.5,71,2,peugeot 304 54 | 30,4,88,76,2065,14.5,71,2,fiat 124b 55 | 31,4,71,65,1773,19,71,3,toyota corolla 1200 56 | 35,4,72,69,1613,18,71,3,datsun 1200 57 | 27,4,97,60,1834,19,71,2,volkswagen model 111 58 | 26,4,91,70,1955,20.5,71,1,plymouth cricket 59 | 24,4,113,95,2278,15.5,72,3,toyota corona hardtop 60 | 25,4,97.5,80,2126,17,72,1,dodge colt hardtop 61 | 23,4,97,54,2254,23.5,72,2,volkswagen type 3 62 | 20,4,140,90,2408,19.5,72,1,chevrolet vega 63 | 21,4,122,86,2226,16.5,72,1,ford pinto runabout 64 | 13,8,350,165,4274,12,72,1,chevrolet impala 65 | 14,8,400,175,4385,12,72,1,pontiac catalina 66 | 15,8,318,150,4135,13.5,72,1,plymouth fury iii 67 | 14,8,351,153,4129,13,72,1,ford galaxie 500 68 | 17,8,304,150,3672,11.5,72,1,amc ambassador sst 69 | 11,8,429,208,4633,11,72,1,mercury marquis 70 | 13,8,350,155,4502,13.5,72,1,buick lesabre custom 71 | 12,8,350,160,4456,13.5,72,1,oldsmobile delta 88 royale 72 | 13,8,400,190,4422,12.5,72,1,chrysler newport royal 73 | 19,3,70,97,2330,13.5,72,3,mazda rx2 coupe 74 | 15,8,304,150,3892,12.5,72,1,amc matador (sw) 75 | 13,8,307,130,4098,14,72,1,chevrolet chevelle concours (sw) 76 | 13,8,302,140,4294,16,72,1,ford gran torino (sw) 77 | 14,8,318,150,4077,14,72,1,plymouth satellite custom (sw) 78 | 18,4,121,112,2933,14.5,72,2,volvo 145e (sw) 79 | 22,4,121,76,2511,18,72,2,volkswagen 411 (sw) 80 | 21,4,120,87,2979,19.5,72,2,peugeot 504 (sw) 81 | 26,4,96,69,2189,18,72,2,renault 12 (sw) 82 | 22,4,122,86,2395,16,72,1,ford pinto (sw) 83 | 28,4,97,92,2288,17,72,3,datsun 510 (sw) 84 | 23,4,120,97,2506,14.5,72,3,toyouta corona mark ii (sw) 85 | 28,4,98,80,2164,15,72,1,dodge colt (sw) 86 | 27,4,97,88,2100,16.5,72,3,toyota corolla 1600 (sw) 87 | 13,8,350,175,4100,13,73,1,buick century 350 88 | 14,8,304,150,3672,11.5,73,1,amc matador 89 | 13,8,350,145,3988,13,73,1,chevrolet malibu 90 | 14,8,302,137,4042,14.5,73,1,ford gran torino 91 | 15,8,318,150,3777,12.5,73,1,dodge coronet custom 92 | 12,8,429,198,4952,11.5,73,1,mercury marquis brougham 93 | 13,8,400,150,4464,12,73,1,chevrolet caprice classic 94 | 13,8,351,158,4363,13,73,1,ford ltd 95 | 14,8,318,150,4237,14.5,73,1,plymouth fury gran sedan 96 | 13,8,440,215,4735,11,73,1,chrysler new yorker brougham 97 | 12,8,455,225,4951,11,73,1,buick electra 225 custom 98 | 13,8,360,175,3821,11,73,1,amc ambassador brougham 99 | 18,6,225,105,3121,16.5,73,1,plymouth valiant 100 | 16,6,250,100,3278,18,73,1,chevrolet nova custom 101 | 18,6,232,100,2945,16,73,1,amc hornet 102 | 18,6,250,88,3021,16.5,73,1,ford maverick 103 | 23,6,198,95,2904,16,73,1,plymouth duster 104 | 26,4,97,46,1950,21,73,2,volkswagen super beetle 105 | 11,8,400,150,4997,14,73,1,chevrolet impala 106 | 12,8,400,167,4906,12.5,73,1,ford country 107 | 13,8,360,170,4654,13,73,1,plymouth custom suburb 108 | 12,8,350,180,4499,12.5,73,1,oldsmobile vista cruiser 109 | 18,6,232,100,2789,15,73,1,amc gremlin 110 | 20,4,97,88,2279,19,73,3,toyota carina 111 | 21,4,140,72,2401,19.5,73,1,chevrolet vega 112 | 22,4,108,94,2379,16.5,73,3,datsun 610 113 | 18,3,70,90,2124,13.5,73,3,maxda rx3 114 | 19,4,122,85,2310,18.5,73,1,ford pinto 115 | 21,6,155,107,2472,14,73,1,mercury capri v6 116 | 26,4,98,90,2265,15.5,73,2,fiat 124 sport coupe 117 | 15,8,350,145,4082,13,73,1,chevrolet monte carlo s 118 | 16,8,400,230,4278,9.5,73,1,pontiac grand prix 119 | 29,4,68,49,1867,19.5,73,2,fiat 128 120 | 24,4,116,75,2158,15.5,73,2,opel manta 121 | 20,4,114,91,2582,14,73,2,audi 100ls 122 | 19,4,121,112,2868,15.5,73,2,volvo 144ea 123 | 15,8,318,150,3399,11,73,1,dodge dart custom 124 | 24,4,121,110,2660,14,73,2,saab 99le 125 | 20,6,156,122,2807,13.5,73,3,toyota mark ii 126 | 11,8,350,180,3664,11,73,1,oldsmobile omega 127 | 20,6,198,95,3102,16.5,74,1,plymouth duster 128 | 21,6,200,?,2875,17,74,1,ford maverick 129 | 19,6,232,100,2901,16,74,1,amc hornet 130 | 15,6,250,100,3336,17,74,1,chevrolet nova 131 | 31,4,79,67,1950,19,74,3,datsun b210 132 | 26,4,122,80,2451,16.5,74,1,ford pinto 133 | 32,4,71,65,1836,21,74,3,toyota corolla 1200 134 | 25,4,140,75,2542,17,74,1,chevrolet vega 135 | 16,6,250,100,3781,17,74,1,chevrolet chevelle malibu classic 136 | 16,6,258,110,3632,18,74,1,amc matador 137 | 18,6,225,105,3613,16.5,74,1,plymouth satellite sebring 138 | 16,8,302,140,4141,14,74,1,ford gran torino 139 | 13,8,350,150,4699,14.5,74,1,buick century luxus (sw) 140 | 14,8,318,150,4457,13.5,74,1,dodge coronet custom (sw) 141 | 14,8,302,140,4638,16,74,1,ford gran torino (sw) 142 | 14,8,304,150,4257,15.5,74,1,amc matador (sw) 143 | 29,4,98,83,2219,16.5,74,2,audi fox 144 | 26,4,79,67,1963,15.5,74,2,volkswagen dasher 145 | 26,4,97,78,2300,14.5,74,2,opel manta 146 | 31,4,76,52,1649,16.5,74,3,toyota corona 147 | 32,4,83,61,2003,19,74,3,datsun 710 148 | 28,4,90,75,2125,14.5,74,1,dodge colt 149 | 24,4,90,75,2108,15.5,74,2,fiat 128 150 | 26,4,116,75,2246,14,74,2,fiat 124 tc 151 | 24,4,120,97,2489,15,74,3,honda civic 152 | 26,4,108,93,2391,15.5,74,3,subaru 153 | 31,4,79,67,2000,16,74,2,fiat x1.9 154 | 19,6,225,95,3264,16,75,1,plymouth valiant custom 155 | 18,6,250,105,3459,16,75,1,chevrolet nova 156 | 15,6,250,72,3432,21,75,1,mercury monarch 157 | 15,6,250,72,3158,19.5,75,1,ford maverick 158 | 16,8,400,170,4668,11.5,75,1,pontiac catalina 159 | 15,8,350,145,4440,14,75,1,chevrolet bel air 160 | 16,8,318,150,4498,14.5,75,1,plymouth grand fury 161 | 14,8,351,148,4657,13.5,75,1,ford ltd 162 | 17,6,231,110,3907,21,75,1,buick century 163 | 16,6,250,105,3897,18.5,75,1,chevroelt chevelle malibu 164 | 15,6,258,110,3730,19,75,1,amc matador 165 | 18,6,225,95,3785,19,75,1,plymouth fury 166 | 21,6,231,110,3039,15,75,1,buick skyhawk 167 | 20,8,262,110,3221,13.5,75,1,chevrolet monza 2+2 168 | 13,8,302,129,3169,12,75,1,ford mustang ii 169 | 29,4,97,75,2171,16,75,3,toyota corolla 170 | 23,4,140,83,2639,17,75,1,ford pinto 171 | 20,6,232,100,2914,16,75,1,amc gremlin 172 | 23,4,140,78,2592,18.5,75,1,pontiac astro 173 | 24,4,134,96,2702,13.5,75,3,toyota corona 174 | 25,4,90,71,2223,16.5,75,2,volkswagen dasher 175 | 24,4,119,97,2545,17,75,3,datsun 710 176 | 18,6,171,97,2984,14.5,75,1,ford pinto 177 | 29,4,90,70,1937,14,75,2,volkswagen rabbit 178 | 19,6,232,90,3211,17,75,1,amc pacer 179 | 23,4,115,95,2694,15,75,2,audi 100ls 180 | 23,4,120,88,2957,17,75,2,peugeot 504 181 | 22,4,121,98,2945,14.5,75,2,volvo 244dl 182 | 25,4,121,115,2671,13.5,75,2,saab 99le 183 | 33,4,91,53,1795,17.5,75,3,honda civic cvcc 184 | 28,4,107,86,2464,15.5,76,2,fiat 131 185 | 25,4,116,81,2220,16.9,76,2,opel 1900 186 | 25,4,140,92,2572,14.9,76,1,capri ii 187 | 26,4,98,79,2255,17.7,76,1,dodge colt 188 | 27,4,101,83,2202,15.3,76,2,renault 12tl 189 | 17.5,8,305,140,4215,13,76,1,chevrolet chevelle malibu classic 190 | 16,8,318,150,4190,13,76,1,dodge coronet brougham 191 | 15.5,8,304,120,3962,13.9,76,1,amc matador 192 | 14.5,8,351,152,4215,12.8,76,1,ford gran torino 193 | 22,6,225,100,3233,15.4,76,1,plymouth valiant 194 | 22,6,250,105,3353,14.5,76,1,chevrolet nova 195 | 24,6,200,81,3012,17.6,76,1,ford maverick 196 | 22.5,6,232,90,3085,17.6,76,1,amc hornet 197 | 29,4,85,52,2035,22.2,76,1,chevrolet chevette 198 | 24.5,4,98,60,2164,22.1,76,1,chevrolet woody 199 | 29,4,90,70,1937,14.2,76,2,vw rabbit 200 | 33,4,91,53,1795,17.4,76,3,honda civic 201 | 20,6,225,100,3651,17.7,76,1,dodge aspen se 202 | 18,6,250,78,3574,21,76,1,ford granada ghia 203 | 18.5,6,250,110,3645,16.2,76,1,pontiac ventura sj 204 | 17.5,6,258,95,3193,17.8,76,1,amc pacer d/l 205 | 29.5,4,97,71,1825,12.2,76,2,volkswagen rabbit 206 | 32,4,85,70,1990,17,76,3,datsun b-210 207 | 28,4,97,75,2155,16.4,76,3,toyota corolla 208 | 26.5,4,140,72,2565,13.6,76,1,ford pinto 209 | 20,4,130,102,3150,15.7,76,2,volvo 245 210 | 13,8,318,150,3940,13.2,76,1,plymouth volare premier v8 211 | 19,4,120,88,3270,21.9,76,2,peugeot 504 212 | 19,6,156,108,2930,15.5,76,3,toyota mark ii 213 | 16.5,6,168,120,3820,16.7,76,2,mercedes-benz 280s 214 | 16.5,8,350,180,4380,12.1,76,1,cadillac seville 215 | 13,8,350,145,4055,12,76,1,chevy c10 216 | 13,8,302,130,3870,15,76,1,ford f108 217 | 13,8,318,150,3755,14,76,1,dodge d100 218 | 31.5,4,98,68,2045,18.5,77,3,honda accord cvcc 219 | 30,4,111,80,2155,14.8,77,1,buick opel isuzu deluxe 220 | 36,4,79,58,1825,18.6,77,2,renault 5 gtl 221 | 25.5,4,122,96,2300,15.5,77,1,plymouth arrow gs 222 | 33.5,4,85,70,1945,16.8,77,3,datsun f-10 hatchback 223 | 17.5,8,305,145,3880,12.5,77,1,chevrolet caprice classic 224 | 17,8,260,110,4060,19,77,1,oldsmobile cutlass supreme 225 | 15.5,8,318,145,4140,13.7,77,1,dodge monaco brougham 226 | 15,8,302,130,4295,14.9,77,1,mercury cougar brougham 227 | 17.5,6,250,110,3520,16.4,77,1,chevrolet concours 228 | 20.5,6,231,105,3425,16.9,77,1,buick skylark 229 | 19,6,225,100,3630,17.7,77,1,plymouth volare custom 230 | 18.5,6,250,98,3525,19,77,1,ford granada 231 | 16,8,400,180,4220,11.1,77,1,pontiac grand prix lj 232 | 15.5,8,350,170,4165,11.4,77,1,chevrolet monte carlo landau 233 | 15.5,8,400,190,4325,12.2,77,1,chrysler cordoba 234 | 16,8,351,149,4335,14.5,77,1,ford thunderbird 235 | 29,4,97,78,1940,14.5,77,2,volkswagen rabbit custom 236 | 24.5,4,151,88,2740,16,77,1,pontiac sunbird coupe 237 | 26,4,97,75,2265,18.2,77,3,toyota corolla liftback 238 | 25.5,4,140,89,2755,15.8,77,1,ford mustang ii 2+2 239 | 30.5,4,98,63,2051,17,77,1,chevrolet chevette 240 | 33.5,4,98,83,2075,15.9,77,1,dodge colt m/m 241 | 30,4,97,67,1985,16.4,77,3,subaru dl 242 | 30.5,4,97,78,2190,14.1,77,2,volkswagen dasher 243 | 22,6,146,97,2815,14.5,77,3,datsun 810 244 | 21.5,4,121,110,2600,12.8,77,2,bmw 320i 245 | 21.5,3,80,110,2720,13.5,77,3,mazda rx-4 246 | 43.1,4,90,48,1985,21.5,78,2,volkswagen rabbit custom diesel 247 | 36.1,4,98,66,1800,14.4,78,1,ford fiesta 248 | 32.8,4,78,52,1985,19.4,78,3,mazda glc deluxe 249 | 39.4,4,85,70,2070,18.6,78,3,datsun b210 gx 250 | 36.1,4,91,60,1800,16.4,78,3,honda civic cvcc 251 | 19.9,8,260,110,3365,15.5,78,1,oldsmobile cutlass salon brougham 252 | 19.4,8,318,140,3735,13.2,78,1,dodge diplomat 253 | 20.2,8,302,139,3570,12.8,78,1,mercury monarch ghia 254 | 19.2,6,231,105,3535,19.2,78,1,pontiac phoenix lj 255 | 20.5,6,200,95,3155,18.2,78,1,chevrolet malibu 256 | 20.2,6,200,85,2965,15.8,78,1,ford fairmont (auto) 257 | 25.1,4,140,88,2720,15.4,78,1,ford fairmont (man) 258 | 20.5,6,225,100,3430,17.2,78,1,plymouth volare 259 | 19.4,6,232,90,3210,17.2,78,1,amc concord 260 | 20.6,6,231,105,3380,15.8,78,1,buick century special 261 | 20.8,6,200,85,3070,16.7,78,1,mercury zephyr 262 | 18.6,6,225,110,3620,18.7,78,1,dodge aspen 263 | 18.1,6,258,120,3410,15.1,78,1,amc concord d/l 264 | 19.2,8,305,145,3425,13.2,78,1,chevrolet monte carlo landau 265 | 17.7,6,231,165,3445,13.4,78,1,buick regal sport coupe (turbo) 266 | 18.1,8,302,139,3205,11.2,78,1,ford futura 267 | 17.5,8,318,140,4080,13.7,78,1,dodge magnum xe 268 | 30,4,98,68,2155,16.5,78,1,chevrolet chevette 269 | 27.5,4,134,95,2560,14.2,78,3,toyota corona 270 | 27.2,4,119,97,2300,14.7,78,3,datsun 510 271 | 30.9,4,105,75,2230,14.5,78,1,dodge omni 272 | 21.1,4,134,95,2515,14.8,78,3,toyota celica gt liftback 273 | 23.2,4,156,105,2745,16.7,78,1,plymouth sapporo 274 | 23.8,4,151,85,2855,17.6,78,1,oldsmobile starfire sx 275 | 23.9,4,119,97,2405,14.9,78,3,datsun 200-sx 276 | 20.3,5,131,103,2830,15.9,78,2,audi 5000 277 | 17,6,163,125,3140,13.6,78,2,volvo 264gl 278 | 21.6,4,121,115,2795,15.7,78,2,saab 99gle 279 | 16.2,6,163,133,3410,15.8,78,2,peugeot 604sl 280 | 31.5,4,89,71,1990,14.9,78,2,volkswagen scirocco 281 | 29.5,4,98,68,2135,16.6,78,3,honda accord lx 282 | 21.5,6,231,115,3245,15.4,79,1,pontiac lemans v6 283 | 19.8,6,200,85,2990,18.2,79,1,mercury zephyr 6 284 | 22.3,4,140,88,2890,17.3,79,1,ford fairmont 4 285 | 20.2,6,232,90,3265,18.2,79,1,amc concord dl 6 286 | 20.6,6,225,110,3360,16.6,79,1,dodge aspen 6 287 | 17,8,305,130,3840,15.4,79,1,chevrolet caprice classic 288 | 17.6,8,302,129,3725,13.4,79,1,ford ltd landau 289 | 16.5,8,351,138,3955,13.2,79,1,mercury grand marquis 290 | 18.2,8,318,135,3830,15.2,79,1,dodge st. regis 291 | 16.9,8,350,155,4360,14.9,79,1,buick estate wagon (sw) 292 | 15.5,8,351,142,4054,14.3,79,1,ford country squire (sw) 293 | 19.2,8,267,125,3605,15,79,1,chevrolet malibu classic (sw) 294 | 18.5,8,360,150,3940,13,79,1,chrysler lebaron town @ country (sw) 295 | 31.9,4,89,71,1925,14,79,2,vw rabbit custom 296 | 34.1,4,86,65,1975,15.2,79,3,maxda glc deluxe 297 | 35.7,4,98,80,1915,14.4,79,1,dodge colt hatchback custom 298 | 27.4,4,121,80,2670,15,79,1,amc spirit dl 299 | 25.4,5,183,77,3530,20.1,79,2,mercedes benz 300d 300 | 23,8,350,125,3900,17.4,79,1,cadillac eldorado 301 | 27.2,4,141,71,3190,24.8,79,2,peugeot 504 302 | 23.9,8,260,90,3420,22.2,79,1,oldsmobile cutlass salon brougham 303 | 34.2,4,105,70,2200,13.2,79,1,plymouth horizon 304 | 34.5,4,105,70,2150,14.9,79,1,plymouth horizon tc3 305 | 31.8,4,85,65,2020,19.2,79,3,datsun 210 306 | 37.3,4,91,69,2130,14.7,79,2,fiat strada custom 307 | 28.4,4,151,90,2670,16,79,1,buick skylark limited 308 | 28.8,6,173,115,2595,11.3,79,1,chevrolet citation 309 | 26.8,6,173,115,2700,12.9,79,1,oldsmobile omega brougham 310 | 33.5,4,151,90,2556,13.2,79,1,pontiac phoenix 311 | 41.5,4,98,76,2144,14.7,80,2,vw rabbit 312 | 38.1,4,89,60,1968,18.8,80,3,toyota corolla tercel 313 | 32.1,4,98,70,2120,15.5,80,1,chevrolet chevette 314 | 37.2,4,86,65,2019,16.4,80,3,datsun 310 315 | 28,4,151,90,2678,16.5,80,1,chevrolet citation 316 | 26.4,4,140,88,2870,18.1,80,1,ford fairmont 317 | 24.3,4,151,90,3003,20.1,80,1,amc concord 318 | 19.1,6,225,90,3381,18.7,80,1,dodge aspen 319 | 34.3,4,97,78,2188,15.8,80,2,audi 4000 320 | 29.8,4,134,90,2711,15.5,80,3,toyota corona liftback 321 | 31.3,4,120,75,2542,17.5,80,3,mazda 626 322 | 37,4,119,92,2434,15,80,3,datsun 510 hatchback 323 | 32.2,4,108,75,2265,15.2,80,3,toyota corolla 324 | 46.6,4,86,65,2110,17.9,80,3,mazda glc 325 | 27.9,4,156,105,2800,14.4,80,1,dodge colt 326 | 40.8,4,85,65,2110,19.2,80,3,datsun 210 327 | 44.3,4,90,48,2085,21.7,80,2,vw rabbit c (diesel) 328 | 43.4,4,90,48,2335,23.7,80,2,vw dasher (diesel) 329 | 36.4,5,121,67,2950,19.9,80,2,audi 5000s (diesel) 330 | 30,4,146,67,3250,21.8,80,2,mercedes-benz 240d 331 | 44.6,4,91,67,1850,13.8,80,3,honda civic 1500 gl 332 | 40.9,4,85,?,1835,17.3,80,2,renault lecar deluxe 333 | 33.8,4,97,67,2145,18,80,3,subaru dl 334 | 29.8,4,89,62,1845,15.3,80,2,vokswagen rabbit 335 | 32.7,6,168,132,2910,11.4,80,3,datsun 280-zx 336 | 23.7,3,70,100,2420,12.5,80,3,mazda rx-7 gs 337 | 35,4,122,88,2500,15.1,80,2,triumph tr7 coupe 338 | 23.6,4,140,?,2905,14.3,80,1,ford mustang cobra 339 | 32.4,4,107,72,2290,17,80,3,honda accord 340 | 27.2,4,135,84,2490,15.7,81,1,plymouth reliant 341 | 26.6,4,151,84,2635,16.4,81,1,buick skylark 342 | 25.8,4,156,92,2620,14.4,81,1,dodge aries wagon (sw) 343 | 23.5,6,173,110,2725,12.6,81,1,chevrolet citation 344 | 30,4,135,84,2385,12.9,81,1,plymouth reliant 345 | 39.1,4,79,58,1755,16.9,81,3,toyota starlet 346 | 39,4,86,64,1875,16.4,81,1,plymouth champ 347 | 35.1,4,81,60,1760,16.1,81,3,honda civic 1300 348 | 32.3,4,97,67,2065,17.8,81,3,subaru 349 | 37,4,85,65,1975,19.4,81,3,datsun 210 mpg 350 | 37.7,4,89,62,2050,17.3,81,3,toyota tercel 351 | 34.1,4,91,68,1985,16,81,3,mazda glc 4 352 | 34.7,4,105,63,2215,14.9,81,1,plymouth horizon 4 353 | 34.4,4,98,65,2045,16.2,81,1,ford escort 4w 354 | 29.9,4,98,65,2380,20.7,81,1,ford escort 2h 355 | 33,4,105,74,2190,14.2,81,2,volkswagen jetta 356 | 34.5,4,100,?,2320,15.8,81,2,renault 18i 357 | 33.7,4,107,75,2210,14.4,81,3,honda prelude 358 | 32.4,4,108,75,2350,16.8,81,3,toyota corolla 359 | 32.9,4,119,100,2615,14.8,81,3,datsun 200sx 360 | 31.6,4,120,74,2635,18.3,81,3,mazda 626 361 | 28.1,4,141,80,3230,20.4,81,2,peugeot 505s turbo diesel 362 | 30.7,6,145,76,3160,19.6,81,2,volvo diesel 363 | 25.4,6,168,116,2900,12.6,81,3,toyota cressida 364 | 24.2,6,146,120,2930,13.8,81,3,datsun 810 maxima 365 | 22.4,6,231,110,3415,15.8,81,1,buick century 366 | 26.6,8,350,105,3725,19,81,1,oldsmobile cutlass ls 367 | 20.2,6,200,88,3060,17.1,81,1,ford granada gl 368 | 17.6,6,225,85,3465,16.6,81,1,chrysler lebaron salon 369 | 28,4,112,88,2605,19.6,82,1,chevrolet cavalier 370 | 27,4,112,88,2640,18.6,82,1,chevrolet cavalier wagon 371 | 34,4,112,88,2395,18,82,1,chevrolet cavalier 2-door 372 | 31,4,112,85,2575,16.2,82,1,pontiac j2000 se hatchback 373 | 29,4,135,84,2525,16,82,1,dodge aries se 374 | 27,4,151,90,2735,18,82,1,pontiac phoenix 375 | 24,4,140,92,2865,16.4,82,1,ford fairmont futura 376 | 36,4,105,74,1980,15.3,82,2,volkswagen rabbit l 377 | 37,4,91,68,2025,18.2,82,3,mazda glc custom l 378 | 31,4,91,68,1970,17.6,82,3,mazda glc custom 379 | 38,4,105,63,2125,14.7,82,1,plymouth horizon miser 380 | 36,4,98,70,2125,17.3,82,1,mercury lynx l 381 | 36,4,120,88,2160,14.5,82,3,nissan stanza xe 382 | 36,4,107,75,2205,14.5,82,3,honda accord 383 | 34,4,108,70,2245,16.9,82,3,toyota corolla 384 | 38,4,91,67,1965,15,82,3,honda civic 385 | 32,4,91,67,1965,15.7,82,3,honda civic (auto) 386 | 38,4,91,67,1995,16.2,82,3,datsun 310 gx 387 | 25,6,181,110,2945,16.4,82,1,buick century limited 388 | 38,6,262,85,3015,17,82,1,oldsmobile cutlass ciera (diesel) 389 | 26,4,156,92,2585,14.5,82,1,chrysler lebaron medallion 390 | 22,6,232,112,2835,14.7,82,1,ford granada l 391 | 32,4,144,96,2665,13.9,82,3,toyota celica gt 392 | 36,4,135,84,2370,13,82,1,dodge charger 2.2 393 | 27,4,151,90,2950,17.3,82,1,chevrolet camaro 394 | 27,4,140,86,2790,15.6,82,1,ford mustang gl 395 | 44,4,97,52,2130,24.6,82,2,vw pickup 396 | 32,4,135,84,2295,11.6,82,1,dodge rampage 397 | 28,4,120,79,2625,18.6,82,1,ford ranger 398 | 31,4,119,82,2720,19.4,82,1,chevy s-10 399 | -------------------------------------------------------------------------------- /datasets/Heart.csv: -------------------------------------------------------------------------------- 1 | "","Age","Sex","ChestPain","RestBP","Chol","Fbs","RestECG","MaxHR","ExAng","Oldpeak","Slope","Ca","Thal","AHD" 2 | "1",63,1,"typical",145,233,1,2,150,0,2.3,3,0,"fixed","No" 3 | "2",67,1,"asymptomatic",160,286,0,2,108,1,1.5,2,3,"normal","Yes" 4 | "3",67,1,"asymptomatic",120,229,0,2,129,1,2.6,2,2,"reversable","Yes" 5 | "4",37,1,"nonanginal",130,250,0,0,187,0,3.5,3,0,"normal","No" 6 | "5",41,0,"nontypical",130,204,0,2,172,0,1.4,1,0,"normal","No" 7 | "6",56,1,"nontypical",120,236,0,0,178,0,0.8,1,0,"normal","No" 8 | "7",62,0,"asymptomatic",140,268,0,2,160,0,3.6,3,2,"normal","Yes" 9 | "8",57,0,"asymptomatic",120,354,0,0,163,1,0.6,1,0,"normal","No" 10 | "9",63,1,"asymptomatic",130,254,0,2,147,0,1.4,2,1,"reversable","Yes" 11 | "10",53,1,"asymptomatic",140,203,1,2,155,1,3.1,3,0,"reversable","Yes" 12 | "11",57,1,"asymptomatic",140,192,0,0,148,0,0.4,2,0,"fixed","No" 13 | "12",56,0,"nontypical",140,294,0,2,153,0,1.3,2,0,"normal","No" 14 | "13",56,1,"nonanginal",130,256,1,2,142,1,0.6,2,1,"fixed","Yes" 15 | "14",44,1,"nontypical",120,263,0,0,173,0,0,1,0,"reversable","No" 16 | "15",52,1,"nonanginal",172,199,1,0,162,0,0.5,1,0,"reversable","No" 17 | "16",57,1,"nonanginal",150,168,0,0,174,0,1.6,1,0,"normal","No" 18 | "17",48,1,"nontypical",110,229,0,0,168,0,1,3,0,"reversable","Yes" 19 | "18",54,1,"asymptomatic",140,239,0,0,160,0,1.2,1,0,"normal","No" 20 | "19",48,0,"nonanginal",130,275,0,0,139,0,0.2,1,0,"normal","No" 21 | "20",49,1,"nontypical",130,266,0,0,171,0,0.6,1,0,"normal","No" 22 | "21",64,1,"typical",110,211,0,2,144,1,1.8,2,0,"normal","No" 23 | "22",58,0,"typical",150,283,1,2,162,0,1,1,0,"normal","No" 24 | "23",58,1,"nontypical",120,284,0,2,160,0,1.8,2,0,"normal","Yes" 25 | "24",58,1,"nonanginal",132,224,0,2,173,0,3.2,1,2,"reversable","Yes" 26 | "25",60,1,"asymptomatic",130,206,0,2,132,1,2.4,2,2,"reversable","Yes" 27 | "26",50,0,"nonanginal",120,219,0,0,158,0,1.6,2,0,"normal","No" 28 | "27",58,0,"nonanginal",120,340,0,0,172,0,0,1,0,"normal","No" 29 | "28",66,0,"typical",150,226,0,0,114,0,2.6,3,0,"normal","No" 30 | "29",43,1,"asymptomatic",150,247,0,0,171,0,1.5,1,0,"normal","No" 31 | "30",40,1,"asymptomatic",110,167,0,2,114,1,2,2,0,"reversable","Yes" 32 | "31",69,0,"typical",140,239,0,0,151,0,1.8,1,2,"normal","No" 33 | "32",60,1,"asymptomatic",117,230,1,0,160,1,1.4,1,2,"reversable","Yes" 34 | "33",64,1,"nonanginal",140,335,0,0,158,0,0,1,0,"normal","Yes" 35 | "34",59,1,"asymptomatic",135,234,0,0,161,0,0.5,2,0,"reversable","No" 36 | "35",44,1,"nonanginal",130,233,0,0,179,1,0.4,1,0,"normal","No" 37 | "36",42,1,"asymptomatic",140,226,0,0,178,0,0,1,0,"normal","No" 38 | "37",43,1,"asymptomatic",120,177,0,2,120,1,2.5,2,0,"reversable","Yes" 39 | "38",57,1,"asymptomatic",150,276,0,2,112,1,0.6,2,1,"fixed","Yes" 40 | "39",55,1,"asymptomatic",132,353,0,0,132,1,1.2,2,1,"reversable","Yes" 41 | "40",61,1,"nonanginal",150,243,1,0,137,1,1,2,0,"normal","No" 42 | "41",65,0,"asymptomatic",150,225,0,2,114,0,1,2,3,"reversable","Yes" 43 | "42",40,1,"typical",140,199,0,0,178,1,1.4,1,0,"reversable","No" 44 | "43",71,0,"nontypical",160,302,0,0,162,0,0.4,1,2,"normal","No" 45 | "44",59,1,"nonanginal",150,212,1,0,157,0,1.6,1,0,"normal","No" 46 | "45",61,0,"asymptomatic",130,330,0,2,169,0,0,1,0,"normal","Yes" 47 | "46",58,1,"nonanginal",112,230,0,2,165,0,2.5,2,1,"reversable","Yes" 48 | "47",51,1,"nonanginal",110,175,0,0,123,0,0.6,1,0,"normal","No" 49 | "48",50,1,"asymptomatic",150,243,0,2,128,0,2.6,2,0,"reversable","Yes" 50 | "49",65,0,"nonanginal",140,417,1,2,157,0,0.8,1,1,"normal","No" 51 | "50",53,1,"nonanginal",130,197,1,2,152,0,1.2,3,0,"normal","No" 52 | "51",41,0,"nontypical",105,198,0,0,168,0,0,1,1,"normal","No" 53 | "52",65,1,"asymptomatic",120,177,0,0,140,0,0.4,1,0,"reversable","No" 54 | "53",44,1,"asymptomatic",112,290,0,2,153,0,0,1,1,"normal","Yes" 55 | "54",44,1,"nontypical",130,219,0,2,188,0,0,1,0,"normal","No" 56 | "55",60,1,"asymptomatic",130,253,0,0,144,1,1.4,1,1,"reversable","Yes" 57 | "56",54,1,"asymptomatic",124,266,0,2,109,1,2.2,2,1,"reversable","Yes" 58 | "57",50,1,"nonanginal",140,233,0,0,163,0,0.6,2,1,"reversable","Yes" 59 | "58",41,1,"asymptomatic",110,172,0,2,158,0,0,1,0,"reversable","Yes" 60 | "59",54,1,"nonanginal",125,273,0,2,152,0,0.5,3,1,"normal","No" 61 | "60",51,1,"typical",125,213,0,2,125,1,1.4,1,1,"normal","No" 62 | "61",51,0,"asymptomatic",130,305,0,0,142,1,1.2,2,0,"reversable","Yes" 63 | "62",46,0,"nonanginal",142,177,0,2,160,1,1.4,3,0,"normal","No" 64 | "63",58,1,"asymptomatic",128,216,0,2,131,1,2.2,2,3,"reversable","Yes" 65 | "64",54,0,"nonanginal",135,304,1,0,170,0,0,1,0,"normal","No" 66 | "65",54,1,"asymptomatic",120,188,0,0,113,0,1.4,2,1,"reversable","Yes" 67 | "66",60,1,"asymptomatic",145,282,0,2,142,1,2.8,2,2,"reversable","Yes" 68 | "67",60,1,"nonanginal",140,185,0,2,155,0,3,2,0,"normal","Yes" 69 | "68",54,1,"nonanginal",150,232,0,2,165,0,1.6,1,0,"reversable","No" 70 | "69",59,1,"asymptomatic",170,326,0,2,140,1,3.4,3,0,"reversable","Yes" 71 | "70",46,1,"nonanginal",150,231,0,0,147,0,3.6,2,0,"normal","Yes" 72 | "71",65,0,"nonanginal",155,269,0,0,148,0,0.8,1,0,"normal","No" 73 | "72",67,1,"asymptomatic",125,254,1,0,163,0,0.2,2,2,"reversable","Yes" 74 | "73",62,1,"asymptomatic",120,267,0,0,99,1,1.8,2,2,"reversable","Yes" 75 | "74",65,1,"asymptomatic",110,248,0,2,158,0,0.6,1,2,"fixed","Yes" 76 | "75",44,1,"asymptomatic",110,197,0,2,177,0,0,1,1,"normal","Yes" 77 | "76",65,0,"nonanginal",160,360,0,2,151,0,0.8,1,0,"normal","No" 78 | "77",60,1,"asymptomatic",125,258,0,2,141,1,2.8,2,1,"reversable","Yes" 79 | "78",51,0,"nonanginal",140,308,0,2,142,0,1.5,1,1,"normal","No" 80 | "79",48,1,"nontypical",130,245,0,2,180,0,0.2,2,0,"normal","No" 81 | "80",58,1,"asymptomatic",150,270,0,2,111,1,0.8,1,0,"reversable","Yes" 82 | "81",45,1,"asymptomatic",104,208,0,2,148,1,3,2,0,"normal","No" 83 | "82",53,0,"asymptomatic",130,264,0,2,143,0,0.4,2,0,"normal","No" 84 | "83",39,1,"nonanginal",140,321,0,2,182,0,0,1,0,"normal","No" 85 | "84",68,1,"nonanginal",180,274,1,2,150,1,1.6,2,0,"reversable","Yes" 86 | "85",52,1,"nontypical",120,325,0,0,172,0,0.2,1,0,"normal","No" 87 | "86",44,1,"nonanginal",140,235,0,2,180,0,0,1,0,"normal","No" 88 | "87",47,1,"nonanginal",138,257,0,2,156,0,0,1,0,"normal","No" 89 | "88",53,0,"nonanginal",128,216,0,2,115,0,0,1,0,NA,"No" 90 | "89",53,0,"asymptomatic",138,234,0,2,160,0,0,1,0,"normal","No" 91 | "90",51,0,"nonanginal",130,256,0,2,149,0,0.5,1,0,"normal","No" 92 | "91",66,1,"asymptomatic",120,302,0,2,151,0,0.4,2,0,"normal","No" 93 | "92",62,0,"asymptomatic",160,164,0,2,145,0,6.2,3,3,"reversable","Yes" 94 | "93",62,1,"nonanginal",130,231,0,0,146,0,1.8,2,3,"reversable","No" 95 | "94",44,0,"nonanginal",108,141,0,0,175,0,0.6,2,0,"normal","No" 96 | "95",63,0,"nonanginal",135,252,0,2,172,0,0,1,0,"normal","No" 97 | "96",52,1,"asymptomatic",128,255,0,0,161,1,0,1,1,"reversable","Yes" 98 | "97",59,1,"asymptomatic",110,239,0,2,142,1,1.2,2,1,"reversable","Yes" 99 | "98",60,0,"asymptomatic",150,258,0,2,157,0,2.6,2,2,"reversable","Yes" 100 | "99",52,1,"nontypical",134,201,0,0,158,0,0.8,1,1,"normal","No" 101 | "100",48,1,"asymptomatic",122,222,0,2,186,0,0,1,0,"normal","No" 102 | "101",45,1,"asymptomatic",115,260,0,2,185,0,0,1,0,"normal","No" 103 | "102",34,1,"typical",118,182,0,2,174,0,0,1,0,"normal","No" 104 | "103",57,0,"asymptomatic",128,303,0,2,159,0,0,1,1,"normal","No" 105 | "104",71,0,"nonanginal",110,265,1,2,130,0,0,1,1,"normal","No" 106 | "105",49,1,"nonanginal",120,188,0,0,139,0,2,2,3,"reversable","Yes" 107 | "106",54,1,"nontypical",108,309,0,0,156,0,0,1,0,"reversable","No" 108 | "107",59,1,"asymptomatic",140,177,0,0,162,1,0,1,1,"reversable","Yes" 109 | "108",57,1,"nonanginal",128,229,0,2,150,0,0.4,2,1,"reversable","Yes" 110 | "109",61,1,"asymptomatic",120,260,0,0,140,1,3.6,2,1,"reversable","Yes" 111 | "110",39,1,"asymptomatic",118,219,0,0,140,0,1.2,2,0,"reversable","Yes" 112 | "111",61,0,"asymptomatic",145,307,0,2,146,1,1,2,0,"reversable","Yes" 113 | "112",56,1,"asymptomatic",125,249,1,2,144,1,1.2,2,1,"normal","Yes" 114 | "113",52,1,"typical",118,186,0,2,190,0,0,2,0,"fixed","No" 115 | "114",43,0,"asymptomatic",132,341,1,2,136,1,3,2,0,"reversable","Yes" 116 | "115",62,0,"nonanginal",130,263,0,0,97,0,1.2,2,1,"reversable","Yes" 117 | "116",41,1,"nontypical",135,203,0,0,132,0,0,2,0,"fixed","No" 118 | "117",58,1,"nonanginal",140,211,1,2,165,0,0,1,0,"normal","No" 119 | "118",35,0,"asymptomatic",138,183,0,0,182,0,1.4,1,0,"normal","No" 120 | "119",63,1,"asymptomatic",130,330,1,2,132,1,1.8,1,3,"reversable","Yes" 121 | "120",65,1,"asymptomatic",135,254,0,2,127,0,2.8,2,1,"reversable","Yes" 122 | "121",48,1,"asymptomatic",130,256,1,2,150,1,0,1,2,"reversable","Yes" 123 | "122",63,0,"asymptomatic",150,407,0,2,154,0,4,2,3,"reversable","Yes" 124 | "123",51,1,"nonanginal",100,222,0,0,143,1,1.2,2,0,"normal","No" 125 | "124",55,1,"asymptomatic",140,217,0,0,111,1,5.6,3,0,"reversable","Yes" 126 | "125",65,1,"typical",138,282,1,2,174,0,1.4,2,1,"normal","Yes" 127 | "126",45,0,"nontypical",130,234,0,2,175,0,0.6,2,0,"normal","No" 128 | "127",56,0,"asymptomatic",200,288,1,2,133,1,4,3,2,"reversable","Yes" 129 | "128",54,1,"asymptomatic",110,239,0,0,126,1,2.8,2,1,"reversable","Yes" 130 | "129",44,1,"nontypical",120,220,0,0,170,0,0,1,0,"normal","No" 131 | "130",62,0,"asymptomatic",124,209,0,0,163,0,0,1,0,"normal","No" 132 | "131",54,1,"nonanginal",120,258,0,2,147,0,0.4,2,0,"reversable","No" 133 | "132",51,1,"nonanginal",94,227,0,0,154,1,0,1,1,"reversable","No" 134 | "133",29,1,"nontypical",130,204,0,2,202,0,0,1,0,"normal","No" 135 | "134",51,1,"asymptomatic",140,261,0,2,186,1,0,1,0,"normal","No" 136 | "135",43,0,"nonanginal",122,213,0,0,165,0,0.2,2,0,"normal","No" 137 | "136",55,0,"nontypical",135,250,0,2,161,0,1.4,2,0,"normal","No" 138 | "137",70,1,"asymptomatic",145,174,0,0,125,1,2.6,3,0,"reversable","Yes" 139 | "138",62,1,"nontypical",120,281,0,2,103,0,1.4,2,1,"reversable","Yes" 140 | "139",35,1,"asymptomatic",120,198,0,0,130,1,1.6,2,0,"reversable","Yes" 141 | "140",51,1,"nonanginal",125,245,1,2,166,0,2.4,2,0,"normal","No" 142 | "141",59,1,"nontypical",140,221,0,0,164,1,0,1,0,"normal","No" 143 | "142",59,1,"typical",170,288,0,2,159,0,0.2,2,0,"reversable","Yes" 144 | "143",52,1,"nontypical",128,205,1,0,184,0,0,1,0,"normal","No" 145 | "144",64,1,"nonanginal",125,309,0,0,131,1,1.8,2,0,"reversable","Yes" 146 | "145",58,1,"nonanginal",105,240,0,2,154,1,0.6,2,0,"reversable","No" 147 | "146",47,1,"nonanginal",108,243,0,0,152,0,0,1,0,"normal","Yes" 148 | "147",57,1,"asymptomatic",165,289,1,2,124,0,1,2,3,"reversable","Yes" 149 | "148",41,1,"nonanginal",112,250,0,0,179,0,0,1,0,"normal","No" 150 | "149",45,1,"nontypical",128,308,0,2,170,0,0,1,0,"normal","No" 151 | "150",60,0,"nonanginal",102,318,0,0,160,0,0,1,1,"normal","No" 152 | "151",52,1,"typical",152,298,1,0,178,0,1.2,2,0,"reversable","No" 153 | "152",42,0,"asymptomatic",102,265,0,2,122,0,0.6,2,0,"normal","No" 154 | "153",67,0,"nonanginal",115,564,0,2,160,0,1.6,2,0,"reversable","No" 155 | "154",55,1,"asymptomatic",160,289,0,2,145,1,0.8,2,1,"reversable","Yes" 156 | "155",64,1,"asymptomatic",120,246,0,2,96,1,2.2,3,1,"normal","Yes" 157 | "156",70,1,"asymptomatic",130,322,0,2,109,0,2.4,2,3,"normal","Yes" 158 | "157",51,1,"asymptomatic",140,299,0,0,173,1,1.6,1,0,"reversable","Yes" 159 | "158",58,1,"asymptomatic",125,300,0,2,171,0,0,1,2,"reversable","Yes" 160 | "159",60,1,"asymptomatic",140,293,0,2,170,0,1.2,2,2,"reversable","Yes" 161 | "160",68,1,"nonanginal",118,277,0,0,151,0,1,1,1,"reversable","No" 162 | "161",46,1,"nontypical",101,197,1,0,156,0,0,1,0,"reversable","No" 163 | "162",77,1,"asymptomatic",125,304,0,2,162,1,0,1,3,"normal","Yes" 164 | "163",54,0,"nonanginal",110,214,0,0,158,0,1.6,2,0,"normal","No" 165 | "164",58,0,"asymptomatic",100,248,0,2,122,0,1,2,0,"normal","No" 166 | "165",48,1,"nonanginal",124,255,1,0,175,0,0,1,2,"normal","No" 167 | "166",57,1,"asymptomatic",132,207,0,0,168,1,0,1,0,"reversable","No" 168 | "167",52,1,"nonanginal",138,223,0,0,169,0,0,1,NA,"normal","No" 169 | "168",54,0,"nontypical",132,288,1,2,159,1,0,1,1,"normal","No" 170 | "169",35,1,"asymptomatic",126,282,0,2,156,1,0,1,0,"reversable","Yes" 171 | "170",45,0,"nontypical",112,160,0,0,138,0,0,2,0,"normal","No" 172 | "171",70,1,"nonanginal",160,269,0,0,112,1,2.9,2,1,"reversable","Yes" 173 | "172",53,1,"asymptomatic",142,226,0,2,111,1,0,1,0,"reversable","No" 174 | "173",59,0,"asymptomatic",174,249,0,0,143,1,0,2,0,"normal","Yes" 175 | "174",62,0,"asymptomatic",140,394,0,2,157,0,1.2,2,0,"normal","No" 176 | "175",64,1,"asymptomatic",145,212,0,2,132,0,2,2,2,"fixed","Yes" 177 | "176",57,1,"asymptomatic",152,274,0,0,88,1,1.2,2,1,"reversable","Yes" 178 | "177",52,1,"asymptomatic",108,233,1,0,147,0,0.1,1,3,"reversable","No" 179 | "178",56,1,"asymptomatic",132,184,0,2,105,1,2.1,2,1,"fixed","Yes" 180 | "179",43,1,"nonanginal",130,315,0,0,162,0,1.9,1,1,"normal","No" 181 | "180",53,1,"nonanginal",130,246,1,2,173,0,0,1,3,"normal","No" 182 | "181",48,1,"asymptomatic",124,274,0,2,166,0,0.5,2,0,"reversable","Yes" 183 | "182",56,0,"asymptomatic",134,409,0,2,150,1,1.9,2,2,"reversable","Yes" 184 | "183",42,1,"typical",148,244,0,2,178,0,0.8,1,2,"normal","No" 185 | "184",59,1,"typical",178,270,0,2,145,0,4.2,3,0,"reversable","No" 186 | "185",60,0,"asymptomatic",158,305,0,2,161,0,0,1,0,"normal","Yes" 187 | "186",63,0,"nontypical",140,195,0,0,179,0,0,1,2,"normal","No" 188 | "187",42,1,"nonanginal",120,240,1,0,194,0,0.8,3,0,"reversable","No" 189 | "188",66,1,"nontypical",160,246,0,0,120,1,0,2,3,"fixed","Yes" 190 | "189",54,1,"nontypical",192,283,0,2,195,0,0,1,1,"reversable","Yes" 191 | "190",69,1,"nonanginal",140,254,0,2,146,0,2,2,3,"reversable","Yes" 192 | "191",50,1,"nonanginal",129,196,0,0,163,0,0,1,0,"normal","No" 193 | "192",51,1,"asymptomatic",140,298,0,0,122,1,4.2,2,3,"reversable","Yes" 194 | "193",43,1,"asymptomatic",132,247,1,2,143,1,0.1,2,NA,"reversable","Yes" 195 | "194",62,0,"asymptomatic",138,294,1,0,106,0,1.9,2,3,"normal","Yes" 196 | "195",68,0,"nonanginal",120,211,0,2,115,0,1.5,2,0,"normal","No" 197 | "196",67,1,"asymptomatic",100,299,0,2,125,1,0.9,2,2,"normal","Yes" 198 | "197",69,1,"typical",160,234,1,2,131,0,0.1,2,1,"normal","No" 199 | "198",45,0,"asymptomatic",138,236,0,2,152,1,0.2,2,0,"normal","No" 200 | "199",50,0,"nontypical",120,244,0,0,162,0,1.1,1,0,"normal","No" 201 | "200",59,1,"typical",160,273,0,2,125,0,0,1,0,"normal","Yes" 202 | "201",50,0,"asymptomatic",110,254,0,2,159,0,0,1,0,"normal","No" 203 | "202",64,0,"asymptomatic",180,325,0,0,154,1,0,1,0,"normal","No" 204 | "203",57,1,"nonanginal",150,126,1,0,173,0,0.2,1,1,"reversable","No" 205 | "204",64,0,"nonanginal",140,313,0,0,133,0,0.2,1,0,"reversable","No" 206 | "205",43,1,"asymptomatic",110,211,0,0,161,0,0,1,0,"reversable","No" 207 | "206",45,1,"asymptomatic",142,309,0,2,147,1,0,2,3,"reversable","Yes" 208 | "207",58,1,"asymptomatic",128,259,0,2,130,1,3,2,2,"reversable","Yes" 209 | "208",50,1,"asymptomatic",144,200,0,2,126,1,0.9,2,0,"reversable","Yes" 210 | "209",55,1,"nontypical",130,262,0,0,155,0,0,1,0,"normal","No" 211 | "210",62,0,"asymptomatic",150,244,0,0,154,1,1.4,2,0,"normal","Yes" 212 | "211",37,0,"nonanginal",120,215,0,0,170,0,0,1,0,"normal","No" 213 | "212",38,1,"typical",120,231,0,0,182,1,3.8,2,0,"reversable","Yes" 214 | "213",41,1,"nonanginal",130,214,0,2,168,0,2,2,0,"normal","No" 215 | "214",66,0,"asymptomatic",178,228,1,0,165,1,1,2,2,"reversable","Yes" 216 | "215",52,1,"asymptomatic",112,230,0,0,160,0,0,1,1,"normal","Yes" 217 | "216",56,1,"typical",120,193,0,2,162,0,1.9,2,0,"reversable","No" 218 | "217",46,0,"nontypical",105,204,0,0,172,0,0,1,0,"normal","No" 219 | "218",46,0,"asymptomatic",138,243,0,2,152,1,0,2,0,"normal","No" 220 | "219",64,0,"asymptomatic",130,303,0,0,122,0,2,2,2,"normal","No" 221 | "220",59,1,"asymptomatic",138,271,0,2,182,0,0,1,0,"normal","No" 222 | "221",41,0,"nonanginal",112,268,0,2,172,1,0,1,0,"normal","No" 223 | "222",54,0,"nonanginal",108,267,0,2,167,0,0,1,0,"normal","No" 224 | "223",39,0,"nonanginal",94,199,0,0,179,0,0,1,0,"normal","No" 225 | "224",53,1,"asymptomatic",123,282,0,0,95,1,2,2,2,"reversable","Yes" 226 | "225",63,0,"asymptomatic",108,269,0,0,169,1,1.8,2,2,"normal","Yes" 227 | "226",34,0,"nontypical",118,210,0,0,192,0,0.7,1,0,"normal","No" 228 | "227",47,1,"asymptomatic",112,204,0,0,143,0,0.1,1,0,"normal","No" 229 | "228",67,0,"nonanginal",152,277,0,0,172,0,0,1,1,"normal","No" 230 | "229",54,1,"asymptomatic",110,206,0,2,108,1,0,2,1,"normal","Yes" 231 | "230",66,1,"asymptomatic",112,212,0,2,132,1,0.1,1,1,"normal","Yes" 232 | "231",52,0,"nonanginal",136,196,0,2,169,0,0.1,2,0,"normal","No" 233 | "232",55,0,"asymptomatic",180,327,0,1,117,1,3.4,2,0,"normal","Yes" 234 | "233",49,1,"nonanginal",118,149,0,2,126,0,0.8,1,3,"normal","Yes" 235 | "234",74,0,"nontypical",120,269,0,2,121,1,0.2,1,1,"normal","No" 236 | "235",54,0,"nonanginal",160,201,0,0,163,0,0,1,1,"normal","No" 237 | "236",54,1,"asymptomatic",122,286,0,2,116,1,3.2,2,2,"normal","Yes" 238 | "237",56,1,"asymptomatic",130,283,1,2,103,1,1.6,3,0,"reversable","Yes" 239 | "238",46,1,"asymptomatic",120,249,0,2,144,0,0.8,1,0,"reversable","Yes" 240 | "239",49,0,"nontypical",134,271,0,0,162,0,0,2,0,"normal","No" 241 | "240",42,1,"nontypical",120,295,0,0,162,0,0,1,0,"normal","No" 242 | "241",41,1,"nontypical",110,235,0,0,153,0,0,1,0,"normal","No" 243 | "242",41,0,"nontypical",126,306,0,0,163,0,0,1,0,"normal","No" 244 | "243",49,0,"asymptomatic",130,269,0,0,163,0,0,1,0,"normal","No" 245 | "244",61,1,"typical",134,234,0,0,145,0,2.6,2,2,"normal","Yes" 246 | "245",60,0,"nonanginal",120,178,1,0,96,0,0,1,0,"normal","No" 247 | "246",67,1,"asymptomatic",120,237,0,0,71,0,1,2,0,"normal","Yes" 248 | "247",58,1,"asymptomatic",100,234,0,0,156,0,0.1,1,1,"reversable","Yes" 249 | "248",47,1,"asymptomatic",110,275,0,2,118,1,1,2,1,"normal","Yes" 250 | "249",52,1,"asymptomatic",125,212,0,0,168,0,1,1,2,"reversable","Yes" 251 | "250",62,1,"nontypical",128,208,1,2,140,0,0,1,0,"normal","No" 252 | "251",57,1,"asymptomatic",110,201,0,0,126,1,1.5,2,0,"fixed","No" 253 | "252",58,1,"asymptomatic",146,218,0,0,105,0,2,2,1,"reversable","Yes" 254 | "253",64,1,"asymptomatic",128,263,0,0,105,1,0.2,2,1,"reversable","No" 255 | "254",51,0,"nonanginal",120,295,0,2,157,0,0.6,1,0,"normal","No" 256 | "255",43,1,"asymptomatic",115,303,0,0,181,0,1.2,2,0,"normal","No" 257 | "256",42,0,"nonanginal",120,209,0,0,173,0,0,2,0,"normal","No" 258 | "257",67,0,"asymptomatic",106,223,0,0,142,0,0.3,1,2,"normal","No" 259 | "258",76,0,"nonanginal",140,197,0,1,116,0,1.1,2,0,"normal","No" 260 | "259",70,1,"nontypical",156,245,0,2,143,0,0,1,0,"normal","No" 261 | "260",57,1,"nontypical",124,261,0,0,141,0,0.3,1,0,"reversable","Yes" 262 | "261",44,0,"nonanginal",118,242,0,0,149,0,0.3,2,1,"normal","No" 263 | "262",58,0,"nontypical",136,319,1,2,152,0,0,1,2,"normal","Yes" 264 | "263",60,0,"typical",150,240,0,0,171,0,0.9,1,0,"normal","No" 265 | "264",44,1,"nonanginal",120,226,0,0,169,0,0,1,0,"normal","No" 266 | "265",61,1,"asymptomatic",138,166,0,2,125,1,3.6,2,1,"normal","Yes" 267 | "266",42,1,"asymptomatic",136,315,0,0,125,1,1.8,2,0,"fixed","Yes" 268 | "267",52,1,"asymptomatic",128,204,1,0,156,1,1,2,0,NA,"Yes" 269 | "268",59,1,"nonanginal",126,218,1,0,134,0,2.2,2,1,"fixed","Yes" 270 | "269",40,1,"asymptomatic",152,223,0,0,181,0,0,1,0,"reversable","Yes" 271 | "270",42,1,"nonanginal",130,180,0,0,150,0,0,1,0,"normal","No" 272 | "271",61,1,"asymptomatic",140,207,0,2,138,1,1.9,1,1,"reversable","Yes" 273 | "272",66,1,"asymptomatic",160,228,0,2,138,0,2.3,1,0,"fixed","No" 274 | "273",46,1,"asymptomatic",140,311,0,0,120,1,1.8,2,2,"reversable","Yes" 275 | "274",71,0,"asymptomatic",112,149,0,0,125,0,1.6,2,0,"normal","No" 276 | "275",59,1,"typical",134,204,0,0,162,0,0.8,1,2,"normal","Yes" 277 | "276",64,1,"typical",170,227,0,2,155,0,0.6,2,0,"reversable","No" 278 | "277",66,0,"nonanginal",146,278,0,2,152,0,0,2,1,"normal","No" 279 | "278",39,0,"nonanginal",138,220,0,0,152,0,0,2,0,"normal","No" 280 | "279",57,1,"nontypical",154,232,0,2,164,0,0,1,1,"normal","Yes" 281 | "280",58,0,"asymptomatic",130,197,0,0,131,0,0.6,2,0,"normal","No" 282 | "281",57,1,"asymptomatic",110,335,0,0,143,1,3,2,1,"reversable","Yes" 283 | "282",47,1,"nonanginal",130,253,0,0,179,0,0,1,0,"normal","No" 284 | "283",55,0,"asymptomatic",128,205,0,1,130,1,2,2,1,"reversable","Yes" 285 | "284",35,1,"nontypical",122,192,0,0,174,0,0,1,0,"normal","No" 286 | "285",61,1,"asymptomatic",148,203,0,0,161,0,0,1,1,"reversable","Yes" 287 | "286",58,1,"asymptomatic",114,318,0,1,140,0,4.4,3,3,"fixed","Yes" 288 | "287",58,0,"asymptomatic",170,225,1,2,146,1,2.8,2,2,"fixed","Yes" 289 | "288",58,1,"nontypical",125,220,0,0,144,0,0.4,2,NA,"reversable","No" 290 | "289",56,1,"nontypical",130,221,0,2,163,0,0,1,0,"reversable","No" 291 | "290",56,1,"nontypical",120,240,0,0,169,0,0,3,0,"normal","No" 292 | "291",67,1,"nonanginal",152,212,0,2,150,0,0.8,2,0,"reversable","Yes" 293 | "292",55,0,"nontypical",132,342,0,0,166,0,1.2,1,0,"normal","No" 294 | "293",44,1,"asymptomatic",120,169,0,0,144,1,2.8,3,0,"fixed","Yes" 295 | "294",63,1,"asymptomatic",140,187,0,2,144,1,4,1,2,"reversable","Yes" 296 | "295",63,0,"asymptomatic",124,197,0,0,136,1,0,2,0,"normal","Yes" 297 | "296",41,1,"nontypical",120,157,0,0,182,0,0,1,0,"normal","No" 298 | "297",59,1,"asymptomatic",164,176,1,2,90,0,1,2,2,"fixed","Yes" 299 | "298",57,0,"asymptomatic",140,241,0,0,123,1,0.2,2,0,"reversable","Yes" 300 | "299",45,1,"typical",110,264,0,0,132,0,1.2,2,0,"reversable","Yes" 301 | "300",68,1,"asymptomatic",144,193,1,0,141,0,3.4,2,2,"reversable","Yes" 302 | "301",57,1,"asymptomatic",130,131,0,0,115,1,1.2,2,1,"reversable","Yes" 303 | "302",57,0,"nontypical",130,236,0,2,174,0,0,2,1,"normal","Yes" 304 | "303",38,1,"nonanginal",138,175,0,0,173,0,0,1,NA,"normal","No" 305 | -------------------------------------------------------------------------------- /data/train_processed.csv: -------------------------------------------------------------------------------- 1 | Survived,Age,Fare,TravelAlone,Pclass_2,Pclass_3,Embarked_Q,Embarked_S,Sex_male 2 | 0,22.0,7.25,0,0,1,0,1,1 3 | 1,38.0,71.2833,0,0,0,0,0,0 4 | 1,26.0,7.925,1,0,1,0,1,0 5 | 1,35.0,53.1,0,0,0,0,1,0 6 | 0,35.0,8.05,1,0,1,0,1,1 7 | 0,28.0,8.4583,1,0,1,1,0,1 8 | 0,54.0,51.8625,1,0,0,0,1,1 9 | 0,2.0,21.075,0,0,1,0,1,1 10 | 1,27.0,11.1333,0,0,1,0,1,0 11 | 1,14.0,30.0708,0,1,0,0,0,0 12 | 1,4.0,16.7,0,0,1,0,1,0 13 | 1,58.0,26.55,1,0,0,0,1,0 14 | 0,20.0,8.05,1,0,1,0,1,1 15 | 0,39.0,31.275,0,0,1,0,1,1 16 | 0,14.0,7.8542,1,0,1,0,1,0 17 | 1,55.0,16.0,1,1,0,0,1,0 18 | 0,2.0,29.125,0,0,1,1,0,1 19 | 1,28.0,13.0,1,1,0,0,1,1 20 | 0,31.0,18.0,0,0,1,0,1,0 21 | 1,28.0,7.225,1,0,1,0,0,0 22 | 0,35.0,26.0,1,1,0,0,1,1 23 | 1,34.0,13.0,1,1,0,0,1,1 24 | 1,15.0,8.0292,1,0,1,1,0,0 25 | 1,28.0,35.5,1,0,0,0,1,1 26 | 0,8.0,21.075,0,0,1,0,1,0 27 | 1,38.0,31.3875,0,0,1,0,1,0 28 | 0,28.0,7.225,1,0,1,0,0,1 29 | 0,19.0,263.0,0,0,0,0,1,1 30 | 1,28.0,7.8792,1,0,1,1,0,0 31 | 0,28.0,7.8958,1,0,1,0,1,1 32 | 0,40.0,27.7208,1,0,0,0,0,1 33 | 1,28.0,146.5208,0,0,0,0,0,0 34 | 1,28.0,7.75,1,0,1,1,0,0 35 | 0,66.0,10.5,1,1,0,0,1,1 36 | 0,28.0,82.1708,0,0,0,0,0,1 37 | 0,42.0,52.0,0,0,0,0,1,1 38 | 1,28.0,7.2292,1,0,1,0,0,1 39 | 0,21.0,8.05,1,0,1,0,1,1 40 | 0,18.0,18.0,0,0,1,0,1,0 41 | 1,14.0,11.2417,0,0,1,0,0,0 42 | 0,40.0,9.475,0,0,1,0,1,0 43 | 0,27.0,21.0,0,1,0,0,1,0 44 | 0,28.0,7.8958,1,0,1,0,0,1 45 | 1,3.0,41.5792,0,1,0,0,0,0 46 | 1,19.0,7.8792,1,0,1,1,0,0 47 | 0,28.0,8.05,1,0,1,0,1,1 48 | 0,28.0,15.5,0,0,1,1,0,1 49 | 1,28.0,7.75,1,0,1,1,0,0 50 | 0,28.0,21.6792,0,0,1,0,0,1 51 | 0,18.0,17.8,0,0,1,0,1,0 52 | 0,7.0,39.6875,0,0,1,0,1,1 53 | 0,21.0,7.8,1,0,1,0,1,1 54 | 1,49.0,76.7292,0,0,0,0,0,0 55 | 1,29.0,26.0,0,1,0,0,1,0 56 | 0,65.0,61.9792,0,0,0,0,0,1 57 | 1,28.0,35.5,1,0,0,0,1,1 58 | 1,21.0,10.5,1,1,0,0,1,0 59 | 0,28.5,7.2292,1,0,1,0,0,1 60 | 1,5.0,27.75,0,1,0,0,1,0 61 | 0,11.0,46.9,0,0,1,0,1,1 62 | 0,22.0,7.2292,1,0,1,0,0,1 63 | 1,38.0,80.0,1,0,0,0,0,0 64 | 0,45.0,83.475,0,0,0,0,1,1 65 | 0,4.0,27.9,0,0,1,0,1,1 66 | 0,28.0,27.7208,1,0,0,0,0,1 67 | 1,28.0,15.2458,0,0,1,0,0,1 68 | 1,29.0,10.5,1,1,0,0,1,0 69 | 0,19.0,8.1583,1,0,1,0,1,1 70 | 1,17.0,7.925,0,0,1,0,1,0 71 | 0,26.0,8.6625,0,0,1,0,1,1 72 | 0,32.0,10.5,1,1,0,0,1,1 73 | 0,16.0,46.9,0,0,1,0,1,0 74 | 0,21.0,73.5,1,1,0,0,1,1 75 | 0,26.0,14.4542,0,0,1,0,0,1 76 | 1,32.0,56.4958,1,0,1,0,1,1 77 | 0,25.0,7.65,1,0,1,0,1,1 78 | 0,28.0,7.8958,1,0,1,0,1,1 79 | 0,28.0,8.05,1,0,1,0,1,1 80 | 1,0.83,29.0,0,1,0,0,1,1 81 | 1,30.0,12.475,1,0,1,0,1,0 82 | 0,22.0,9.0,1,0,1,0,1,1 83 | 1,29.0,9.5,1,0,1,0,1,1 84 | 1,28.0,7.7875,1,0,1,1,0,0 85 | 0,28.0,47.1,1,0,0,0,1,1 86 | 1,17.0,10.5,1,1,0,0,1,0 87 | 1,33.0,15.85,0,0,1,0,1,0 88 | 0,16.0,34.375,0,0,1,0,1,1 89 | 0,28.0,8.05,1,0,1,0,1,1 90 | 1,23.0,263.0,0,0,0,0,1,0 91 | 0,24.0,8.05,1,0,1,0,1,1 92 | 0,29.0,8.05,1,0,1,0,1,1 93 | 0,20.0,7.8542,1,0,1,0,1,1 94 | 0,46.0,61.175,0,0,0,0,1,1 95 | 0,26.0,20.575,0,0,1,0,1,1 96 | 0,59.0,7.25,1,0,1,0,1,1 97 | 0,28.0,8.05,1,0,1,0,1,1 98 | 0,71.0,34.6542,1,0,0,0,0,1 99 | 1,23.0,63.3583,0,0,0,0,0,1 100 | 1,34.0,23.0,0,1,0,0,1,0 101 | 0,34.0,26.0,0,1,0,0,1,1 102 | 0,28.0,7.8958,1,0,1,0,1,0 103 | 0,28.0,7.8958,1,0,1,0,1,1 104 | 0,21.0,77.2875,0,0,0,0,1,1 105 | 0,33.0,8.6542,1,0,1,0,1,1 106 | 0,37.0,7.925,0,0,1,0,1,1 107 | 0,28.0,7.8958,1,0,1,0,1,1 108 | 1,21.0,7.65,1,0,1,0,1,0 109 | 1,28.0,7.775,1,0,1,0,1,1 110 | 0,38.0,7.8958,1,0,1,0,1,1 111 | 1,28.0,24.15,0,0,1,1,0,0 112 | 0,47.0,52.0,1,0,0,0,1,1 113 | 0,14.5,14.4542,0,0,1,0,0,0 114 | 0,22.0,8.05,1,0,1,0,1,1 115 | 0,20.0,9.825,0,0,1,0,1,0 116 | 0,17.0,14.4583,1,0,1,0,0,0 117 | 0,21.0,7.925,1,0,1,0,1,1 118 | 0,70.5,7.75,1,0,1,1,0,1 119 | 0,29.0,21.0,0,1,0,0,1,1 120 | 0,24.0,247.5208,0,0,0,0,0,1 121 | 0,2.0,31.275,0,0,1,0,1,0 122 | 0,21.0,73.5,0,1,0,0,1,1 123 | 0,28.0,8.05,1,0,1,0,1,1 124 | 0,32.5,30.0708,0,1,0,0,0,1 125 | 1,32.5,13.0,1,1,0,0,1,0 126 | 0,54.0,77.2875,0,0,0,0,1,1 127 | 1,12.0,11.2417,0,0,1,0,0,1 128 | 0,28.0,7.75,1,0,1,1,0,1 129 | 1,24.0,7.1417,1,0,1,0,1,1 130 | 1,28.0,22.3583,0,0,1,0,0,0 131 | 0,45.0,6.975,1,0,1,0,1,1 132 | 0,33.0,7.8958,1,0,1,0,0,1 133 | 0,20.0,7.05,1,0,1,0,1,1 134 | 0,47.0,14.5,0,0,1,0,1,0 135 | 1,29.0,26.0,0,1,0,0,1,0 136 | 0,25.0,13.0,1,1,0,0,1,1 137 | 0,23.0,15.0458,1,1,0,0,0,1 138 | 1,19.0,26.2833,0,0,0,0,1,0 139 | 0,37.0,53.1,0,0,0,0,1,1 140 | 0,16.0,9.2167,1,0,1,0,1,1 141 | 0,24.0,79.2,1,0,0,0,0,1 142 | 0,28.0,15.2458,0,0,1,0,0,0 143 | 1,22.0,7.75,1,0,1,0,1,0 144 | 1,24.0,15.85,0,0,1,0,1,0 145 | 0,19.0,6.75,1,0,1,1,0,1 146 | 0,18.0,11.5,1,1,0,0,1,1 147 | 0,19.0,36.75,0,1,0,0,1,1 148 | 1,27.0,7.7958,1,0,1,0,1,1 149 | 0,9.0,34.375,0,0,1,0,1,0 150 | 0,36.5,26.0,0,1,0,0,1,1 151 | 0,42.0,13.0,1,1,0,0,1,1 152 | 0,51.0,12.525,1,1,0,0,1,1 153 | 1,22.0,66.6,0,0,0,0,1,0 154 | 0,55.5,8.05,1,0,1,0,1,1 155 | 0,40.5,14.5,0,0,1,0,1,1 156 | 0,28.0,7.3125,1,0,1,0,1,1 157 | 0,51.0,61.3792,0,0,0,0,0,1 158 | 1,16.0,7.7333,1,0,1,1,0,0 159 | 0,30.0,8.05,1,0,1,0,1,1 160 | 0,28.0,8.6625,1,0,1,0,1,1 161 | 0,28.0,69.55,0,0,1,0,1,1 162 | 0,44.0,16.1,0,0,1,0,1,1 163 | 1,40.0,15.75,1,1,0,0,1,0 164 | 0,26.0,7.775,1,0,1,0,1,1 165 | 0,17.0,8.6625,1,0,1,0,1,1 166 | 0,1.0,39.6875,0,0,1,0,1,1 167 | 1,9.0,20.525,0,0,1,0,1,1 168 | 1,28.0,55.0,0,0,0,0,1,0 169 | 0,45.0,27.9,0,0,1,0,1,0 170 | 0,28.0,25.925,1,0,0,0,1,1 171 | 0,28.0,56.4958,1,0,1,0,1,1 172 | 0,61.0,33.5,1,0,0,0,1,1 173 | 0,4.0,29.125,0,0,1,1,0,1 174 | 1,1.0,11.1333,0,0,1,0,1,0 175 | 0,21.0,7.925,1,0,1,0,1,1 176 | 0,56.0,30.6958,1,0,0,0,0,1 177 | 0,18.0,7.8542,0,0,1,0,1,1 178 | 0,28.0,25.4667,0,0,1,0,1,1 179 | 0,50.0,28.7125,1,0,0,0,0,0 180 | 0,30.0,13.0,1,1,0,0,1,1 181 | 0,28.0,69.55,0,0,1,0,1,0 182 | 0,28.0,15.05,1,1,0,0,0,1 183 | 0,9.0,31.3875,0,0,1,0,1,1 184 | 1,1.0,39.0,0,1,0,0,1,1 185 | 1,4.0,22.025,0,0,1,0,1,0 186 | 0,28.0,50.0,1,0,0,0,1,1 187 | 1,28.0,15.5,0,0,1,1,0,0 188 | 1,45.0,26.55,1,0,0,0,1,1 189 | 0,40.0,15.5,0,0,1,1,0,1 190 | 0,36.0,7.8958,1,0,1,0,1,1 191 | 1,32.0,13.0,1,1,0,0,1,0 192 | 0,19.0,13.0,1,1,0,0,1,1 193 | 1,19.0,7.8542,0,0,1,0,1,0 194 | 1,3.0,26.0,0,1,0,0,1,1 195 | 1,44.0,27.7208,1,0,0,0,0,0 196 | 1,58.0,146.5208,1,0,0,0,0,0 197 | 0,28.0,7.75,1,0,1,1,0,1 198 | 0,42.0,8.4042,0,0,1,0,1,1 199 | 1,28.0,7.75,1,0,1,1,0,0 200 | 0,24.0,13.0,1,1,0,0,1,0 201 | 0,28.0,9.5,1,0,1,0,1,1 202 | 0,28.0,69.55,0,0,1,0,1,1 203 | 0,34.0,6.4958,1,0,1,0,1,1 204 | 0,45.5,7.225,1,0,1,0,0,1 205 | 1,18.0,8.05,1,0,1,0,1,1 206 | 0,2.0,10.4625,0,0,1,0,1,0 207 | 0,32.0,15.85,0,0,1,0,1,1 208 | 1,26.0,18.7875,1,0,1,0,0,1 209 | 1,16.0,7.75,1,0,1,1,0,0 210 | 1,40.0,31.0,1,0,0,0,0,1 211 | 0,24.0,7.05,1,0,1,0,1,1 212 | 1,35.0,21.0,1,1,0,0,1,0 213 | 0,22.0,7.25,1,0,1,0,1,1 214 | 0,30.0,13.0,1,1,0,0,1,1 215 | 0,28.0,7.75,0,0,1,1,0,1 216 | 1,31.0,113.275,0,0,0,0,0,0 217 | 1,27.0,7.925,1,0,1,0,1,0 218 | 0,42.0,27.0,0,1,0,0,1,1 219 | 1,32.0,76.2917,1,0,0,0,0,0 220 | 0,30.0,10.5,1,1,0,0,1,1 221 | 1,16.0,8.05,1,0,1,0,1,1 222 | 0,27.0,13.0,1,1,0,0,1,1 223 | 0,51.0,8.05,1,0,1,0,1,1 224 | 0,28.0,7.8958,1,0,1,0,1,1 225 | 1,38.0,90.0,0,0,0,0,1,1 226 | 0,22.0,9.35,1,0,1,0,1,1 227 | 1,19.0,10.5,1,1,0,0,1,1 228 | 0,20.5,7.25,1,0,1,0,1,1 229 | 0,18.0,13.0,1,1,0,0,1,1 230 | 0,28.0,25.4667,0,0,1,0,1,0 231 | 1,35.0,83.475,0,0,0,0,1,0 232 | 0,29.0,7.775,1,0,1,0,1,1 233 | 0,59.0,13.5,1,1,0,0,1,1 234 | 1,5.0,31.3875,0,0,1,0,1,0 235 | 0,24.0,10.5,1,1,0,0,1,1 236 | 0,28.0,7.55,1,0,1,0,1,0 237 | 0,44.0,26.0,0,1,0,0,1,1 238 | 1,8.0,26.25,0,1,0,0,1,0 239 | 0,19.0,10.5,1,1,0,0,1,1 240 | 0,33.0,12.275,1,1,0,0,1,1 241 | 0,28.0,14.4542,0,0,1,0,0,0 242 | 1,28.0,15.5,0,0,1,1,0,0 243 | 0,29.0,10.5,1,1,0,0,1,1 244 | 0,22.0,7.125,1,0,1,0,1,1 245 | 0,30.0,7.225,1,0,1,0,0,1 246 | 0,44.0,90.0,0,0,0,1,0,1 247 | 0,25.0,7.775,1,0,1,0,1,0 248 | 1,24.0,14.5,0,1,0,0,1,0 249 | 1,37.0,52.5542,0,0,0,0,1,1 250 | 0,54.0,26.0,0,1,0,0,1,1 251 | 0,28.0,7.25,1,0,1,0,1,1 252 | 0,29.0,10.4625,0,0,1,0,1,0 253 | 0,62.0,26.55,1,0,0,0,1,1 254 | 0,30.0,16.1,0,0,1,0,1,1 255 | 0,41.0,20.2125,0,0,1,0,1,0 256 | 1,29.0,15.2458,0,0,1,0,0,0 257 | 1,28.0,79.2,1,0,0,0,0,0 258 | 1,30.0,86.5,1,0,0,0,1,0 259 | 1,35.0,512.3292,1,0,0,0,0,0 260 | 1,50.0,26.0,0,1,0,0,1,0 261 | 0,28.0,7.75,1,0,1,1,0,1 262 | 1,3.0,31.3875,0,0,1,0,1,1 263 | 0,52.0,79.65,0,0,0,0,1,1 264 | 0,28.0,7.75,1,0,1,1,0,0 265 | 0,36.0,10.5,1,1,0,0,1,1 266 | 0,16.0,39.6875,0,0,1,0,1,1 267 | 1,25.0,7.775,0,0,1,0,1,1 268 | 1,58.0,153.4625,0,0,0,0,1,0 269 | 1,35.0,135.6333,1,0,0,0,1,0 270 | 0,28.0,31.0,1,0,0,0,1,1 271 | 1,41.0,19.5,0,1,0,0,1,0 272 | 0,37.0,29.7,0,0,0,0,0,1 273 | 1,28.0,7.75,1,0,1,1,0,0 274 | 1,63.0,77.9583,0,0,0,0,1,0 275 | 0,45.0,7.75,1,0,1,0,1,0 276 | 0,7.0,29.125,0,0,1,1,0,1 277 | 1,35.0,20.25,0,0,1,0,1,0 278 | 0,65.0,7.75,1,0,1,1,0,1 279 | 0,28.0,7.8542,1,0,1,0,1,1 280 | 0,16.0,9.5,1,0,1,0,1,1 281 | 1,19.0,8.05,1,0,1,0,1,1 282 | 0,28.0,26.0,1,0,0,0,1,1 283 | 0,33.0,8.6625,1,0,1,0,0,1 284 | 1,30.0,9.5,1,0,1,0,1,1 285 | 0,22.0,7.8958,1,0,1,0,1,1 286 | 1,42.0,13.0,1,1,0,0,1,1 287 | 1,22.0,7.75,1,0,1,1,0,0 288 | 1,26.0,78.85,1,0,0,0,1,0 289 | 1,19.0,91.0792,0,0,0,0,0,0 290 | 0,36.0,12.875,1,1,0,0,0,1 291 | 0,24.0,8.85,1,0,1,0,1,0 292 | 0,24.0,7.8958,1,0,1,0,1,1 293 | 0,28.0,27.7208,1,0,0,0,0,1 294 | 0,23.5,7.2292,1,0,1,0,0,1 295 | 0,2.0,151.55,0,0,0,0,1,0 296 | 1,28.0,30.5,1,0,0,0,1,1 297 | 1,50.0,247.5208,0,0,0,0,0,0 298 | 1,28.0,7.75,1,0,1,1,0,0 299 | 1,28.0,23.25,0,0,1,1,0,1 300 | 1,28.0,12.35,1,1,0,1,0,0 301 | 0,28.0,8.05,1,0,1,0,1,1 302 | 1,0.92,151.55,0,0,0,0,1,1 303 | 1,28.0,110.8833,1,0,0,0,0,0 304 | 1,17.0,108.9,0,0,0,0,0,0 305 | 0,30.0,24.0,0,1,0,0,0,1 306 | 1,30.0,56.9292,1,0,0,0,0,0 307 | 1,24.0,83.1583,1,0,0,0,0,0 308 | 1,18.0,262.375,0,0,0,0,0,0 309 | 0,26.0,26.0,0,1,0,0,1,0 310 | 0,28.0,7.8958,1,0,1,0,1,1 311 | 0,43.0,26.25,0,1,0,0,1,1 312 | 1,26.0,7.8542,1,0,1,0,1,0 313 | 1,24.0,26.0,0,1,0,0,1,0 314 | 0,54.0,14.0,1,1,0,0,1,1 315 | 1,31.0,164.8667,0,0,0,0,1,0 316 | 1,40.0,134.5,0,0,0,0,0,0 317 | 0,22.0,7.25,1,0,1,0,1,1 318 | 0,27.0,7.8958,1,0,1,0,1,1 319 | 1,30.0,12.35,1,1,0,1,0,0 320 | 1,22.0,29.0,0,1,0,0,1,0 321 | 0,28.0,69.55,0,0,1,0,1,1 322 | 1,36.0,135.6333,1,0,0,0,0,0 323 | 0,61.0,6.2375,1,0,1,0,1,1 324 | 1,36.0,13.0,1,1,0,0,1,0 325 | 1,31.0,20.525,0,0,1,0,1,0 326 | 1,16.0,57.9792,0,0,0,0,0,0 327 | 1,28.0,23.25,0,0,1,1,0,0 328 | 0,45.5,28.5,1,0,0,0,1,1 329 | 0,38.0,153.4625,0,0,0,0,1,1 330 | 0,16.0,18.0,0,0,1,0,1,1 331 | 1,28.0,133.65,0,0,0,0,1,0 332 | 0,28.0,7.8958,1,0,1,0,1,1 333 | 0,29.0,66.6,0,0,0,0,1,1 334 | 1,41.0,134.5,1,0,0,0,0,0 335 | 1,45.0,8.05,1,0,1,0,1,1 336 | 0,45.0,35.5,1,0,0,0,1,1 337 | 1,2.0,26.0,0,1,0,0,1,1 338 | 1,24.0,263.0,0,0,0,0,1,0 339 | 0,28.0,13.0,1,1,0,0,1,1 340 | 0,25.0,13.0,1,1,0,0,1,1 341 | 0,36.0,13.0,1,1,0,0,1,1 342 | 1,24.0,13.0,1,1,0,0,1,0 343 | 1,40.0,13.0,1,1,0,0,1,0 344 | 1,28.0,16.1,0,0,1,0,1,0 345 | 1,3.0,15.9,0,0,1,0,1,1 346 | 0,42.0,8.6625,1,0,1,0,1,1 347 | 0,23.0,9.225,1,0,1,0,1,1 348 | 0,28.0,35.0,1,0,0,0,1,1 349 | 0,15.0,7.2292,0,0,1,0,0,1 350 | 0,25.0,17.8,0,0,1,0,1,1 351 | 0,28.0,7.225,1,0,1,0,0,1 352 | 0,28.0,9.5,1,0,1,0,1,1 353 | 1,22.0,55.0,0,0,0,0,1,0 354 | 0,38.0,13.0,1,1,0,0,1,0 355 | 1,28.0,7.8792,1,0,1,1,0,0 356 | 1,28.0,7.8792,1,0,1,1,0,0 357 | 0,40.0,27.9,0,0,1,0,1,1 358 | 0,29.0,27.7208,0,1,0,0,0,1 359 | 0,45.0,14.4542,0,0,1,0,0,0 360 | 0,35.0,7.05,1,0,1,0,1,1 361 | 0,28.0,15.5,0,0,1,1,0,1 362 | 0,30.0,7.25,1,0,1,0,1,1 363 | 1,60.0,75.25,0,0,0,0,0,0 364 | 1,28.0,7.2292,1,0,1,0,0,0 365 | 1,28.0,7.75,1,0,1,1,0,0 366 | 1,24.0,69.3,1,0,0,0,0,0 367 | 1,25.0,55.4417,0,0,0,0,0,1 368 | 0,18.0,6.4958,0,0,1,0,1,1 369 | 0,19.0,8.05,1,0,1,0,1,1 370 | 0,22.0,135.6333,1,0,0,0,0,1 371 | 0,3.0,21.075,0,0,1,0,1,0 372 | 1,28.0,82.1708,0,0,0,0,0,0 373 | 1,22.0,7.25,1,0,1,0,1,0 374 | 0,27.0,211.5,0,0,0,0,0,1 375 | 0,20.0,4.0125,1,0,1,0,0,1 376 | 0,19.0,7.775,1,0,1,0,1,1 377 | 1,42.0,227.525,1,0,0,0,0,0 378 | 1,1.0,15.7417,0,0,1,0,0,0 379 | 0,32.0,7.925,1,0,1,0,1,1 380 | 1,35.0,52.0,0,0,0,0,1,0 381 | 0,28.0,7.8958,1,0,1,0,1,1 382 | 0,18.0,73.5,1,1,0,0,1,1 383 | 0,1.0,46.9,0,0,1,0,1,1 384 | 1,36.0,13.0,1,1,0,0,1,0 385 | 0,28.0,7.7292,1,0,1,1,0,1 386 | 1,17.0,12.0,1,1,0,0,0,0 387 | 1,36.0,120.0,0,0,0,0,1,1 388 | 1,21.0,7.7958,1,0,1,0,1,1 389 | 0,28.0,7.925,0,0,1,0,1,1 390 | 1,23.0,113.275,0,0,0,0,0,0 391 | 1,24.0,16.7,0,0,1,0,1,0 392 | 0,22.0,7.7958,1,0,1,0,1,1 393 | 0,31.0,7.8542,1,0,1,0,1,0 394 | 0,46.0,26.0,1,1,0,0,1,1 395 | 0,23.0,10.5,1,1,0,0,1,1 396 | 1,28.0,12.65,1,1,0,0,1,0 397 | 1,39.0,7.925,1,0,1,0,1,1 398 | 0,26.0,8.05,1,0,1,0,1,1 399 | 0,21.0,9.825,0,0,1,0,1,0 400 | 0,28.0,15.85,0,0,1,0,1,1 401 | 0,20.0,8.6625,1,0,1,0,1,0 402 | 0,34.0,21.0,0,1,0,0,1,1 403 | 0,51.0,7.75,1,0,1,0,1,1 404 | 1,3.0,18.75,0,1,0,0,1,1 405 | 0,21.0,7.775,1,0,1,0,1,1 406 | 0,28.0,25.4667,0,0,1,0,1,0 407 | 0,28.0,7.8958,1,0,1,0,1,1 408 | 0,28.0,6.8583,1,0,1,1,0,1 409 | 1,33.0,90.0,0,0,0,1,0,0 410 | 1,44.0,7.925,1,0,1,0,1,1 411 | 0,28.0,8.05,1,0,1,0,1,0 412 | 1,34.0,32.5,0,1,0,0,1,0 413 | 1,18.0,13.0,0,1,0,0,1,0 414 | 0,30.0,13.0,1,1,0,0,1,1 415 | 0,10.0,24.15,0,0,1,0,1,0 416 | 0,28.0,7.8958,1,0,1,0,0,1 417 | 0,21.0,7.7333,1,0,1,1,0,1 418 | 0,29.0,7.875,1,0,1,0,1,1 419 | 0,28.0,14.4,0,0,1,0,1,0 420 | 0,18.0,20.2125,0,0,1,0,1,1 421 | 0,28.0,7.25,1,0,1,0,1,1 422 | 1,28.0,26.0,0,1,0,0,1,0 423 | 1,19.0,26.0,1,1,0,0,1,0 424 | 0,28.0,7.75,1,0,1,1,0,1 425 | 1,32.0,8.05,1,0,1,0,1,1 426 | 1,28.0,26.55,1,0,0,0,1,1 427 | 1,28.0,16.1,0,0,1,0,1,0 428 | 1,42.0,26.0,0,1,0,0,1,0 429 | 0,17.0,7.125,1,0,1,0,1,1 430 | 0,50.0,55.9,0,0,0,0,1,1 431 | 1,14.0,120.0,0,0,0,0,1,0 432 | 0,21.0,34.375,0,0,1,0,1,0 433 | 1,24.0,18.75,0,1,0,0,1,0 434 | 0,64.0,263.0,0,0,0,0,1,1 435 | 0,31.0,10.5,1,1,0,0,1,1 436 | 1,45.0,26.25,0,1,0,0,1,0 437 | 0,20.0,9.5,1,0,1,0,1,1 438 | 0,25.0,7.775,0,0,1,0,1,1 439 | 1,28.0,13.0,1,1,0,0,1,0 440 | 1,28.0,8.1125,1,0,1,0,1,1 441 | 1,4.0,81.8583,0,0,0,0,1,1 442 | 1,13.0,19.5,0,1,0,0,1,0 443 | 1,34.0,26.55,1,0,0,0,1,1 444 | 1,5.0,19.2583,0,0,1,0,0,0 445 | 1,52.0,30.5,1,0,0,0,1,1 446 | 0,36.0,27.75,0,1,0,0,1,1 447 | 0,28.0,19.9667,0,0,1,0,1,1 448 | 0,30.0,27.75,1,0,0,0,0,1 449 | 1,49.0,89.1042,0,0,0,0,0,1 450 | 0,28.0,8.05,1,0,1,0,1,1 451 | 1,29.0,7.8958,1,0,1,0,0,1 452 | 0,65.0,26.55,1,0,0,0,1,1 453 | 1,28.0,51.8625,0,0,0,0,1,0 454 | 1,50.0,10.5,1,1,0,0,1,0 455 | 0,28.0,7.75,1,0,1,1,0,1 456 | 1,48.0,26.55,1,0,0,0,1,1 457 | 0,34.0,8.05,1,0,1,0,1,1 458 | 0,47.0,38.5,1,0,0,0,1,1 459 | 0,48.0,13.0,1,1,0,0,1,1 460 | 0,28.0,8.05,1,0,1,0,1,1 461 | 0,38.0,7.05,1,0,1,0,1,1 462 | 0,56.0,26.55,1,0,0,0,1,1 463 | 0,28.0,7.725,1,0,1,1,0,1 464 | 1,0.75,19.2583,0,0,1,0,0,0 465 | 0,28.0,7.25,1,0,1,0,1,1 466 | 0,38.0,8.6625,1,0,1,0,1,1 467 | 1,33.0,27.75,0,1,0,0,1,0 468 | 1,23.0,13.7917,1,1,0,0,0,0 469 | 0,22.0,9.8375,1,0,1,0,1,0 470 | 0,28.0,52.0,1,0,0,0,1,1 471 | 0,34.0,21.0,0,1,0,0,1,1 472 | 0,29.0,7.0458,0,0,1,0,1,1 473 | 0,22.0,7.5208,1,0,1,0,1,1 474 | 1,2.0,12.2875,0,0,1,0,1,0 475 | 0,9.0,46.9,0,0,1,0,1,1 476 | 0,50.0,8.05,1,0,1,0,1,1 477 | 1,63.0,9.5875,1,0,1,0,1,0 478 | 1,25.0,91.0792,0,0,0,0,0,1 479 | 0,28.0,25.4667,0,0,1,0,1,0 480 | 1,35.0,90.0,0,0,0,0,1,0 481 | 0,58.0,29.7,1,0,0,0,0,1 482 | 0,30.0,8.05,1,0,1,0,1,1 483 | 1,9.0,15.9,0,0,1,0,1,1 484 | 0,28.0,19.9667,0,0,1,0,1,1 485 | 0,21.0,7.25,1,0,1,0,1,1 486 | 0,55.0,30.5,1,0,0,0,1,1 487 | 0,71.0,49.5042,1,0,0,0,0,1 488 | 0,21.0,8.05,1,0,1,0,1,1 489 | 0,28.0,14.4583,1,0,1,0,0,1 490 | 1,54.0,78.2667,0,0,0,0,0,0 491 | 0,28.0,15.1,1,0,1,0,1,1 492 | 0,25.0,151.55,0,0,0,0,1,0 493 | 0,24.0,7.7958,1,0,1,0,1,1 494 | 0,17.0,8.6625,1,0,1,0,1,1 495 | 0,21.0,7.75,1,0,1,1,0,0 496 | 0,28.0,7.6292,1,0,1,1,0,0 497 | 0,37.0,9.5875,1,0,1,0,1,0 498 | 1,16.0,86.5,1,0,0,0,1,0 499 | 0,18.0,108.9,0,0,0,0,0,1 500 | 1,33.0,26.0,0,1,0,0,1,0 501 | 1,28.0,26.55,1,0,0,0,1,1 502 | 0,28.0,22.525,1,0,1,0,1,1 503 | 1,26.0,56.4958,1,0,1,0,1,1 504 | 1,29.0,7.75,1,0,1,1,0,1 505 | 0,28.0,8.05,1,0,1,0,1,1 506 | 1,36.0,26.2875,1,0,0,0,1,1 507 | 1,54.0,59.4,0,0,0,0,0,0 508 | 0,24.0,7.4958,1,0,1,0,1,1 509 | 0,47.0,34.0208,1,0,0,0,1,1 510 | 1,34.0,10.5,1,1,0,0,1,0 511 | 0,28.0,24.15,1,0,1,1,0,1 512 | 1,36.0,26.0,0,1,0,0,1,0 513 | 0,32.0,7.8958,1,0,1,0,1,1 514 | 1,30.0,93.5,1,0,0,0,1,0 515 | 0,22.0,7.8958,1,0,1,0,1,1 516 | 0,28.0,7.225,1,0,1,0,0,1 517 | 1,44.0,57.9792,0,0,0,0,0,0 518 | 0,28.0,7.2292,1,0,1,0,0,1 519 | 0,40.5,7.75,1,0,1,1,0,1 520 | 1,50.0,10.5,1,1,0,0,1,0 521 | 0,28.0,221.7792,1,0,0,0,1,1 522 | 0,39.0,7.925,1,0,1,0,1,1 523 | 0,23.0,11.5,0,1,0,0,1,1 524 | 1,2.0,26.0,0,1,0,0,1,0 525 | 0,28.0,7.2292,1,0,1,0,0,1 526 | 0,17.0,7.2292,0,0,1,0,0,1 527 | 1,28.0,22.3583,0,0,1,0,0,0 528 | 0,30.0,8.6625,1,0,1,0,1,0 529 | 1,7.0,26.25,0,1,0,0,1,0 530 | 0,45.0,26.55,1,0,0,0,1,1 531 | 1,30.0,106.425,1,0,0,0,0,0 532 | 0,28.0,14.5,1,0,1,0,1,1 533 | 1,22.0,49.5,0,0,0,0,0,0 534 | 1,36.0,71.0,0,0,0,0,1,0 535 | 0,9.0,31.275,0,0,1,0,1,0 536 | 0,11.0,31.275,0,0,1,0,1,0 537 | 1,32.0,26.0,0,1,0,0,1,1 538 | 0,50.0,106.425,0,0,0,0,0,1 539 | 0,64.0,26.0,1,0,0,0,1,1 540 | 1,19.0,26.0,0,1,0,0,1,0 541 | 1,28.0,13.8625,1,1,0,0,0,1 542 | 0,33.0,20.525,0,0,1,0,1,1 543 | 1,8.0,36.75,0,1,0,0,1,1 544 | 1,17.0,110.8833,0,0,0,0,0,1 545 | 0,27.0,26.0,1,1,0,0,1,1 546 | 0,28.0,7.8292,1,0,1,1,0,1 547 | 1,22.0,7.225,1,0,1,0,0,1 548 | 1,22.0,7.775,1,0,1,0,1,0 549 | 0,62.0,26.55,1,0,0,0,1,1 550 | 1,48.0,39.6,0,0,0,0,0,0 551 | 0,28.0,227.525,1,0,0,0,0,1 552 | 1,39.0,79.65,0,0,0,0,1,0 553 | 1,36.0,17.4,0,0,1,0,1,0 554 | 0,28.0,7.75,1,0,1,1,0,1 555 | 0,40.0,7.8958,1,0,1,0,1,1 556 | 0,28.0,13.5,1,1,0,0,1,1 557 | 0,28.0,8.05,1,0,1,0,1,1 558 | 0,28.0,8.05,1,0,1,0,1,0 559 | 0,24.0,24.15,0,0,1,0,1,1 560 | 0,19.0,7.8958,1,0,1,0,1,1 561 | 0,29.0,21.075,0,0,1,0,1,0 562 | 0,28.0,7.2292,1,0,1,0,0,1 563 | 1,32.0,7.8542,1,0,1,0,1,1 564 | 1,62.0,10.5,1,1,0,0,1,1 565 | 1,53.0,51.4792,0,0,0,0,1,0 566 | 1,36.0,26.3875,1,0,0,0,1,1 567 | 1,28.0,7.75,1,0,1,1,0,0 568 | 0,16.0,8.05,1,0,1,0,1,1 569 | 0,19.0,14.5,1,0,1,0,1,1 570 | 1,34.0,13.0,1,1,0,0,1,0 571 | 1,39.0,55.9,0,0,0,0,1,0 572 | 0,28.0,14.4583,0,0,1,0,0,0 573 | 1,32.0,7.925,1,0,1,0,1,1 574 | 1,25.0,30.0,0,1,0,0,1,0 575 | 1,39.0,110.8833,0,0,0,0,0,0 576 | 0,54.0,26.0,1,1,0,0,1,1 577 | 0,36.0,40.125,1,0,0,0,0,1 578 | 0,28.0,8.7125,1,0,1,0,0,1 579 | 1,18.0,79.65,0,0,0,0,1,0 580 | 0,47.0,15.0,1,1,0,0,1,1 581 | 1,60.0,79.2,0,0,0,0,0,1 582 | 0,22.0,8.05,1,0,1,0,1,1 583 | 0,28.0,8.05,1,0,1,0,1,1 584 | 0,35.0,7.125,1,0,1,0,1,1 585 | 1,52.0,78.2667,0,0,0,0,0,0 586 | 0,47.0,7.25,1,0,1,0,1,1 587 | 0,28.0,7.75,0,0,1,1,0,0 588 | 0,37.0,26.0,0,1,0,0,1,1 589 | 0,36.0,24.15,0,0,1,0,1,1 590 | 1,28.0,33.0,1,1,0,0,1,0 591 | 0,28.0,7.225,1,0,1,0,0,1 592 | 1,49.0,56.9292,0,0,0,0,0,1 593 | 1,24.0,27.0,0,1,0,0,1,0 594 | 0,28.0,7.8958,1,0,1,0,1,1 595 | 0,28.0,42.4,1,0,0,0,1,1 596 | 0,44.0,8.05,1,0,1,0,1,1 597 | 1,35.0,26.55,1,0,0,0,0,1 598 | 0,36.0,15.55,0,0,1,0,1,1 599 | 0,30.0,7.8958,1,0,1,0,1,1 600 | 1,27.0,30.5,1,0,0,0,1,1 601 | 1,22.0,41.5792,0,1,0,0,0,0 602 | 1,40.0,153.4625,1,0,0,0,1,0 603 | 0,39.0,31.275,0,0,1,0,1,0 604 | 0,28.0,7.05,1,0,1,0,1,1 605 | 1,28.0,15.5,0,0,1,1,0,0 606 | 0,28.0,7.75,1,0,1,1,0,1 607 | 0,35.0,8.05,1,0,1,0,1,1 608 | 1,24.0,65.0,0,1,0,0,1,0 609 | 0,34.0,14.4,0,0,1,0,1,1 610 | 0,26.0,16.1,0,0,1,0,1,0 611 | 1,4.0,39.0,0,1,0,0,1,0 612 | 0,26.0,10.5,1,1,0,0,1,1 613 | 0,27.0,14.4542,0,0,1,0,0,1 614 | 1,42.0,52.5542,0,0,0,0,1,1 615 | 1,20.0,15.7417,0,0,1,0,0,1 616 | 0,21.0,7.8542,1,0,1,0,1,1 617 | 0,21.0,16.1,1,0,1,0,1,1 618 | 0,61.0,32.3208,1,0,0,0,1,1 619 | 0,57.0,12.35,1,1,0,1,0,1 620 | 1,21.0,77.9583,1,0,0,0,1,0 621 | 0,26.0,7.8958,1,0,1,0,1,1 622 | 0,28.0,7.7333,1,0,1,1,0,1 623 | 1,80.0,30.0,1,0,0,0,1,1 624 | 0,51.0,7.0542,1,0,1,0,1,1 625 | 1,32.0,30.5,1,0,0,0,0,1 626 | 0,9.0,27.9,0,0,1,0,1,0 627 | 1,28.0,13.0,1,1,0,0,1,0 628 | 0,32.0,7.925,1,0,1,0,1,1 629 | 0,31.0,26.25,0,1,0,0,1,1 630 | 0,41.0,39.6875,0,0,1,0,1,0 631 | 0,28.0,16.1,0,0,1,0,1,1 632 | 0,20.0,7.8542,1,0,1,0,1,1 633 | 1,24.0,69.3,1,0,0,0,0,0 634 | 0,2.0,27.9,0,0,1,0,1,0 635 | 1,28.0,56.4958,1,0,1,0,1,1 636 | 1,0.75,19.2583,0,0,1,0,0,0 637 | 1,48.0,76.7292,0,0,0,0,0,1 638 | 0,19.0,7.8958,1,0,1,0,1,1 639 | 1,56.0,35.5,1,0,0,0,0,1 640 | 0,28.0,7.55,1,0,1,0,1,1 641 | 1,23.0,7.55,1,0,1,0,1,0 642 | 0,28.0,7.8958,1,0,1,0,1,1 643 | 1,18.0,23.0,0,1,0,0,1,0 644 | 0,21.0,8.4333,1,0,1,0,1,1 645 | 1,28.0,7.8292,1,0,1,1,0,0 646 | 0,18.0,6.75,1,0,1,1,0,0 647 | 0,24.0,73.5,0,1,0,0,1,1 648 | 0,28.0,7.8958,1,0,1,0,1,1 649 | 0,32.0,15.5,0,0,1,1,0,0 650 | 0,23.0,13.0,1,1,0,0,1,1 651 | 0,58.0,113.275,0,0,0,0,0,1 652 | 1,50.0,133.65,0,0,0,0,1,1 653 | 0,40.0,7.225,1,0,1,0,0,1 654 | 0,47.0,25.5875,1,0,0,0,1,1 655 | 0,36.0,7.4958,1,0,1,0,1,1 656 | 1,20.0,7.925,0,0,1,0,1,1 657 | 0,32.0,73.5,0,1,0,0,1,1 658 | 0,25.0,13.0,1,1,0,0,1,1 659 | 0,28.0,7.775,1,0,1,0,1,1 660 | 0,43.0,8.05,1,0,1,0,1,1 661 | 1,28.0,52.0,0,0,0,0,1,0 662 | 1,40.0,39.0,0,1,0,0,1,0 663 | 0,31.0,52.0,0,0,0,0,1,1 664 | 0,70.0,10.5,1,1,0,0,1,1 665 | 1,31.0,13.0,1,1,0,0,1,1 666 | 0,18.0,7.775,1,0,1,0,1,1 667 | 0,24.5,8.05,1,0,1,0,1,1 668 | 1,18.0,9.8417,1,0,1,0,1,0 669 | 0,43.0,46.9,0,0,1,0,1,0 670 | 1,36.0,512.3292,0,0,0,0,0,1 671 | 0,28.0,8.1375,1,0,1,1,0,0 672 | 1,27.0,76.7292,1,0,0,0,0,1 673 | 0,20.0,9.225,1,0,1,0,1,1 674 | 0,14.0,46.9,0,0,1,0,1,1 675 | 0,60.0,39.0,0,1,0,0,1,1 676 | 0,25.0,41.5792,0,1,0,0,0,1 677 | 0,14.0,39.6875,0,0,1,0,1,1 678 | 0,19.0,10.1708,1,0,1,0,1,1 679 | 0,18.0,7.7958,1,0,1,0,1,1 680 | 1,15.0,211.3375,0,0,0,0,1,0 681 | 1,31.0,57.0,0,0,0,0,1,1 682 | 1,4.0,13.4167,0,0,1,0,0,0 683 | 1,28.0,56.4958,1,0,1,0,1,1 684 | 0,25.0,7.225,1,0,1,0,0,1 685 | 0,60.0,26.55,1,0,0,0,1,1 686 | 0,52.0,13.5,1,1,0,0,1,1 687 | 0,44.0,8.05,1,0,1,0,1,1 688 | 1,28.0,7.7333,1,0,1,1,0,0 689 | 0,49.0,110.8833,0,0,0,0,0,1 690 | 0,42.0,7.65,1,0,1,0,1,1 691 | 1,18.0,227.525,0,0,0,0,0,0 692 | 1,35.0,26.2875,1,0,0,0,1,1 693 | 0,18.0,14.4542,0,0,1,0,0,0 694 | 0,25.0,7.7417,1,0,1,1,0,1 695 | 0,26.0,7.8542,0,0,1,0,1,1 696 | 0,39.0,26.0,1,1,0,0,1,1 697 | 1,45.0,13.5,1,1,0,0,1,0 698 | 1,42.0,26.2875,1,0,0,0,1,1 699 | 1,22.0,151.55,1,0,0,0,1,0 700 | 1,28.0,15.2458,0,0,1,0,0,1 701 | 1,24.0,49.5042,1,0,0,0,0,0 702 | 0,28.0,26.55,1,0,0,0,1,1 703 | 1,48.0,52.0,0,0,0,0,1,1 704 | 0,29.0,9.4833,1,0,1,0,1,1 705 | 0,52.0,13.0,1,1,0,0,1,1 706 | 0,19.0,7.65,1,0,1,0,1,1 707 | 1,38.0,227.525,1,0,0,0,0,0 708 | 1,27.0,10.5,1,1,0,0,1,0 709 | 0,28.0,15.5,1,0,1,1,0,1 710 | 0,33.0,7.775,1,0,1,0,1,1 711 | 1,6.0,33.0,0,1,0,0,1,0 712 | 0,17.0,7.0542,0,0,1,0,1,1 713 | 0,34.0,13.0,1,1,0,0,1,1 714 | 0,50.0,13.0,1,1,0,0,1,1 715 | 1,27.0,53.1,0,0,0,0,1,1 716 | 0,20.0,8.6625,1,0,1,0,1,1 717 | 1,30.0,21.0,0,1,0,0,1,0 718 | 1,28.0,7.7375,1,0,1,1,0,0 719 | 0,25.0,26.0,0,1,0,0,1,1 720 | 0,25.0,7.925,0,0,1,0,1,0 721 | 1,29.0,211.3375,1,0,0,0,1,0 722 | 0,11.0,18.7875,1,0,1,0,0,1 723 | 0,23.0,13.0,1,1,0,0,1,1 724 | 0,23.0,13.0,1,1,0,0,1,1 725 | 0,28.5,16.1,1,0,1,0,1,1 726 | 0,48.0,34.375,0,0,1,0,1,0 727 | 1,35.0,512.3292,1,0,0,0,0,1 728 | 0,28.0,7.8958,1,0,1,0,1,1 729 | 0,28.0,7.8958,1,0,1,0,1,1 730 | 1,28.0,30.0,1,0,0,0,1,1 731 | 0,36.0,78.85,0,0,0,0,1,1 732 | 1,21.0,262.375,0,0,0,0,0,0 733 | 0,24.0,16.1,0,0,1,0,1,1 734 | 1,31.0,7.925,1,0,1,0,1,1 735 | 0,70.0,71.0,0,0,0,0,1,1 736 | 0,16.0,20.25,0,0,1,0,1,1 737 | 1,30.0,13.0,1,1,0,0,1,0 738 | 0,19.0,53.1,0,0,0,0,1,1 739 | 0,31.0,7.75,1,0,1,1,0,1 740 | 1,4.0,23.0,0,1,0,0,1,0 741 | 1,6.0,12.475,0,0,1,0,1,1 742 | 0,33.0,9.5,1,0,1,0,1,1 743 | 0,23.0,7.8958,1,0,1,0,1,1 744 | 1,48.0,65.0,0,1,0,0,1,0 745 | 1,0.67,14.5,0,1,0,0,1,1 746 | 0,28.0,7.7958,1,0,1,0,1,1 747 | 0,18.0,11.5,1,1,0,0,1,1 748 | 0,34.0,8.05,1,0,1,0,1,1 749 | 1,33.0,86.5,1,0,0,0,1,0 750 | 0,28.0,14.5,1,0,1,0,1,1 751 | 0,41.0,7.125,1,0,1,0,1,1 752 | 1,20.0,7.2292,1,0,1,0,0,1 753 | 1,36.0,120.0,0,0,0,0,1,0 754 | 0,16.0,7.775,1,0,1,0,1,1 755 | 1,51.0,77.9583,0,0,0,0,1,0 756 | 0,28.0,39.6,1,0,0,0,0,1 757 | 0,30.5,7.75,1,0,1,1,0,0 758 | 0,28.0,24.15,0,0,1,1,0,1 759 | 0,32.0,8.3625,1,0,1,0,1,1 760 | 0,24.0,9.5,1,0,1,0,1,1 761 | 0,48.0,7.8542,1,0,1,0,1,1 762 | 0,57.0,10.5,1,1,0,0,1,0 763 | 0,28.0,7.225,1,0,1,0,0,1 764 | 1,54.0,23.0,0,1,0,0,1,0 765 | 0,18.0,7.75,1,0,1,0,1,1 766 | 0,28.0,7.75,1,0,1,1,0,1 767 | 1,5.0,12.475,1,0,1,0,1,0 768 | 0,28.0,7.7375,1,0,1,1,0,1 769 | 1,43.0,211.3375,0,0,0,0,1,0 770 | 1,13.0,7.2292,1,0,1,0,0,0 771 | 1,17.0,57.0,0,0,0,0,1,0 772 | 0,29.0,30.0,1,0,0,0,1,1 773 | 0,28.0,23.45,0,0,1,0,1,1 774 | 0,25.0,7.05,1,0,1,0,1,1 775 | 0,25.0,7.25,1,0,1,0,1,1 776 | 1,18.0,7.4958,1,0,1,0,1,0 777 | 0,8.0,29.125,0,0,1,1,0,1 778 | 1,1.0,20.575,0,0,1,0,1,1 779 | 0,46.0,79.2,1,0,0,0,0,1 780 | 0,28.0,7.75,1,0,1,1,0,1 781 | 0,16.0,26.0,1,1,0,0,1,1 782 | 0,28.0,69.55,0,0,1,0,1,0 783 | 0,28.0,30.6958,1,0,0,0,0,1 784 | 0,25.0,7.8958,1,0,1,0,1,1 785 | 0,39.0,13.0,1,1,0,0,1,1 786 | 1,49.0,25.9292,1,0,0,0,1,0 787 | 1,31.0,8.6833,1,0,1,0,1,0 788 | 0,30.0,7.2292,1,0,1,0,0,1 789 | 0,30.0,24.15,0,0,1,0,1,0 790 | 0,34.0,13.0,1,1,0,0,1,1 791 | 1,31.0,26.25,0,1,0,0,1,0 792 | 1,11.0,120.0,0,0,0,0,1,1 793 | 1,0.42,8.5167,0,0,1,0,0,1 794 | 1,27.0,6.975,1,0,1,0,1,1 795 | 0,31.0,7.775,1,0,1,0,1,1 796 | 0,18.0,7.775,1,0,1,0,1,0 797 | 0,39.0,13.0,1,1,0,0,1,1 798 | 1,33.0,53.1,0,0,0,0,1,0 799 | 0,26.0,7.8875,1,0,1,0,1,1 800 | 0,39.0,24.15,1,0,1,0,1,1 801 | 0,35.0,10.5,1,1,0,0,1,1 802 | 0,6.0,31.275,0,0,1,0,1,0 803 | 0,30.5,8.05,1,0,1,0,1,1 804 | 0,23.0,7.925,1,0,1,0,1,0 805 | 0,31.0,37.0042,0,1,0,0,0,1 806 | 0,43.0,6.45,1,0,1,0,1,1 807 | 0,10.0,27.9,0,0,1,0,1,1 808 | 1,52.0,93.5,0,0,0,0,1,0 809 | 1,27.0,8.6625,1,0,1,0,1,1 810 | 1,27.0,12.475,0,0,1,0,1,0 811 | 0,2.0,39.6875,0,0,1,0,1,1 812 | 0,28.0,6.95,1,0,1,1,0,1 813 | 0,28.0,56.4958,1,0,1,0,1,1 814 | 1,1.0,37.0042,0,1,0,0,0,1 815 | 1,28.0,7.75,1,0,1,1,0,1 816 | 1,62.0,80.0,1,0,0,0,0,0 817 | 1,15.0,14.4542,0,0,1,0,0,0 818 | 1,0.83,18.75,0,1,0,0,1,1 819 | 0,28.0,7.2292,1,0,1,0,0,1 820 | 0,23.0,7.8542,1,0,1,0,1,1 821 | 0,18.0,8.3,1,0,1,0,1,1 822 | 1,39.0,83.1583,0,0,0,0,0,0 823 | 0,21.0,8.6625,1,0,1,0,1,1 824 | 0,28.0,8.05,1,0,1,0,1,1 825 | 1,32.0,56.4958,1,0,1,0,1,1 826 | 1,28.0,29.7,1,0,0,0,0,1 827 | 0,20.0,7.925,1,0,1,0,1,1 828 | 0,16.0,10.5,1,1,0,0,1,1 829 | 1,30.0,31.0,1,0,0,0,0,0 830 | 0,34.5,6.4375,1,0,1,0,0,1 831 | 0,17.0,8.6625,1,0,1,0,1,1 832 | 0,42.0,7.55,1,0,1,0,1,1 833 | 0,28.0,69.55,0,0,1,0,1,1 834 | 0,35.0,7.8958,1,0,1,0,0,1 835 | 0,28.0,33.0,0,1,0,0,1,1 836 | 1,28.0,89.1042,0,0,0,0,0,0 837 | 0,4.0,31.275,0,0,1,0,1,1 838 | 0,74.0,7.775,1,0,1,0,1,1 839 | 0,9.0,15.2458,0,0,1,0,0,0 840 | 1,16.0,39.4,0,0,0,0,1,0 841 | 0,44.0,26.0,0,1,0,0,1,0 842 | 1,18.0,9.35,0,0,1,0,1,0 843 | 1,45.0,164.8667,0,0,0,0,1,0 844 | 1,51.0,26.55,1,0,0,0,1,1 845 | 1,24.0,19.2583,0,0,1,0,0,0 846 | 0,28.0,7.2292,1,0,1,0,0,1 847 | 0,41.0,14.1083,0,0,1,0,1,1 848 | 0,21.0,11.5,0,1,0,0,1,1 849 | 1,48.0,25.9292,1,0,0,0,1,0 850 | 0,28.0,69.55,0,0,1,0,1,0 851 | 0,24.0,13.0,1,1,0,0,1,1 852 | 1,42.0,13.0,1,1,0,0,1,0 853 | 1,27.0,13.8583,0,1,0,0,0,0 854 | 0,31.0,50.4958,1,0,0,0,1,1 855 | 0,28.0,9.5,1,0,1,0,1,1 856 | 1,4.0,11.1333,0,0,1,0,1,1 857 | 0,26.0,7.8958,1,0,1,0,1,1 858 | 1,47.0,52.5542,0,0,0,0,1,0 859 | 0,33.0,5.0,1,0,0,0,1,1 860 | 0,47.0,9.0,1,0,1,0,1,1 861 | 1,28.0,24.0,0,1,0,0,0,0 862 | 1,15.0,7.225,1,0,1,0,0,0 863 | 0,20.0,9.8458,1,0,1,0,1,1 864 | 0,19.0,7.8958,1,0,1,0,1,1 865 | 0,28.0,7.8958,1,0,1,0,1,1 866 | 1,56.0,83.1583,0,0,0,0,0,0 867 | 1,25.0,26.0,0,1,0,0,1,0 868 | 0,33.0,7.8958,1,0,1,0,1,1 869 | 0,22.0,10.5167,1,0,1,0,1,0 870 | 0,28.0,10.5,1,1,0,0,1,1 871 | 0,25.0,7.05,1,0,1,0,1,1 872 | 0,39.0,29.125,0,0,1,1,0,0 873 | 0,27.0,13.0,1,1,0,0,1,1 874 | 1,19.0,30.0,1,0,0,0,1,0 875 | 0,28.0,23.45,0,0,1,0,1,0 876 | 1,26.0,30.0,1,0,0,0,0,1 877 | 0,32.0,7.75,1,0,1,1,0,1 878 | -------------------------------------------------------------------------------- /Box-Tidwell-Test-in-R.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# Logistic Regression Assumptions\n", 8 | "### Box-Tidwell Test\n", 9 | "- Using R to perform Box-Tidwell Test (or Assumption 2: Linearity of independent variables and log odds)\n", 10 | "- Details on how to setup R kernel in Jupyter notebook: https://dzone.com/articles/using-r-on-jupyternbspnotebook\n", 11 | "- We are using R here because Python does not have any native packages that executes Box Tidwell transformation directly\n", 12 | "___\n", 13 | "\n", 14 | "- One of the important assumptions of logistic regression is the linearity of the logit over the covariates. When this assumption is not met, a Box-Tidwell transformation might be helpful. \n", 15 | "- The Box-Tidwell Test is used to check this assumption by testing whether the logit transform is a linear function of the predictor, effectively by adding the non-linear transform of the original predictor as an interaction term to test if this addition made no better prediction.\n", 16 | "- A significant p-value in the Box-Tidwell transformation means that the linearity assumption is **violated**\n", 17 | "- If one variable is indeed found to be non-linear, then we may need to incorporate higher order polynomial terms for that variable in the regression analysis to capture the non-linearity\n", 18 | "\n", 19 | "#### References\n", 20 | "- https://stats.stackexchange.com/questions/503906/solution-in-case-of-violation-of-the-linearity-assumption-in-the-logistic-regres\n", 21 | "- https://www.youtube.com/watch?v=sciPFNcYqi8&ab_channel=MikeCrowson" 22 | ] 23 | }, 24 | { 25 | "cell_type": "code", 26 | "execution_count": 1, 27 | "metadata": { 28 | "scrolled": true 29 | }, 30 | "outputs": [ 31 | { 32 | "name": "stderr", 33 | "output_type": "stream", 34 | "text": [ 35 | "Installing package into 'C:/Users/kenne/Documents/R/win-library/4.1'\n", 36 | "(as 'lib' is unspecified)\n", 37 | "\n" 38 | ] 39 | }, 40 | { 41 | "name": "stdout", 42 | "output_type": "stream", 43 | "text": [ 44 | "package 'car' successfully unpacked and MD5 sums checked\n", 45 | "\n", 46 | "The downloaded binary packages are in\n", 47 | "\tC:\\Users\\kenne\\AppData\\Local\\Temp\\RtmpsdMeYP\\downloaded_packages\n" 48 | ] 49 | }, 50 | { 51 | "name": "stderr", 52 | "output_type": "stream", 53 | "text": [ 54 | "Installing package into 'C:/Users/kenne/Documents/R/win-library/4.1'\n", 55 | "(as 'lib' is unspecified)\n", 56 | "\n" 57 | ] 58 | }, 59 | { 60 | "name": "stdout", 61 | "output_type": "stream", 62 | "text": [ 63 | "package 'tidyverse' successfully unpacked and MD5 sums checked\n", 64 | "\n", 65 | "The downloaded binary packages are in\n", 66 | "\tC:\\Users\\kenne\\AppData\\Local\\Temp\\RtmpsdMeYP\\downloaded_packages\n" 67 | ] 68 | } 69 | ], 70 | "source": [ 71 | "# Installing car package to make use of the box tidwell function within\n", 72 | "install.packages(\"car\")\n", 73 | "install.packages(\"tidyverse\")" 74 | ] 75 | }, 76 | { 77 | "cell_type": "code", 78 | "execution_count": 2, 79 | "metadata": {}, 80 | "outputs": [ 81 | { 82 | "name": "stderr", 83 | "output_type": "stream", 84 | "text": [ 85 | "Loading required package: carData\n", 86 | "\n" 87 | ] 88 | } 89 | ], 90 | "source": [ 91 | "library(car)\n", 92 | "library(ggplot2)" 93 | ] 94 | }, 95 | { 96 | "cell_type": "code", 97 | "execution_count": 9, 98 | "metadata": {}, 99 | "outputs": [ 100 | { 101 | "data": { 102 | "text/html": [ 103 | "\n", 104 | "\n", 105 | "\n", 106 | "\t\n", 107 | "\t\n", 108 | "\n", 109 | "\n", 110 | "\t\n", 111 | "\t\n", 112 | "\t\n", 113 | "\t\n", 114 | "\t\n", 115 | "\t\n", 116 | "\n", 117 | "
A data.frame: 6 × 8
SurvivedAgeTravelAlonePclass_2Pclass_3Embarked_QEmbarked_SSex_male
<int><dbl><int><int><int><int><int><int>
1022001011
2138000000
3126101010
4135000010
5035101011
6028101101
\n" 118 | ], 119 | "text/latex": [ 120 | "A data.frame: 6 × 8\n", 121 | "\\begin{tabular}{r|llllllll}\n", 122 | " & Survived & Age & TravelAlone & Pclass\\_2 & Pclass\\_3 & Embarked\\_Q & Embarked\\_S & Sex\\_male\\\\\n", 123 | " & & & & & & & & \\\\\n", 124 | "\\hline\n", 125 | "\t1 & 0 & 22 & 0 & 0 & 1 & 0 & 1 & 1\\\\\n", 126 | "\t2 & 1 & 38 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", 127 | "\t3 & 1 & 26 & 1 & 0 & 1 & 0 & 1 & 0\\\\\n", 128 | "\t4 & 1 & 35 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n", 129 | "\t5 & 0 & 35 & 1 & 0 & 1 & 0 & 1 & 1\\\\\n", 130 | "\t6 & 0 & 28 & 1 & 0 & 1 & 1 & 0 & 1\\\\\n", 131 | "\\end{tabular}\n" 132 | ], 133 | "text/markdown": [ 134 | "\n", 135 | "A data.frame: 6 × 8\n", 136 | "\n", 137 | "| | Survived <int> | Age <dbl> | TravelAlone <int> | Pclass_2 <int> | Pclass_3 <int> | Embarked_Q <int> | Embarked_S <int> | Sex_male <int> |\n", 138 | "|---|---|---|---|---|---|---|---|---|\n", 139 | "| 1 | 0 | 22 | 0 | 0 | 1 | 0 | 1 | 1 |\n", 140 | "| 2 | 1 | 38 | 0 | 0 | 0 | 0 | 0 | 0 |\n", 141 | "| 3 | 1 | 26 | 1 | 0 | 1 | 0 | 1 | 0 |\n", 142 | "| 4 | 1 | 35 | 0 | 0 | 0 | 0 | 1 | 0 |\n", 143 | "| 5 | 0 | 35 | 1 | 0 | 1 | 0 | 1 | 1 |\n", 144 | "| 6 | 0 | 28 | 1 | 0 | 1 | 1 | 0 | 1 |\n", 145 | "\n" 146 | ], 147 | "text/plain": [ 148 | " Survived Age TravelAlone Pclass_2 Pclass_3 Embarked_Q Embarked_S Sex_male\n", 149 | "1 0 22 0 0 1 0 1 1 \n", 150 | "2 1 38 0 0 0 0 0 0 \n", 151 | "3 1 26 1 0 1 0 1 0 \n", 152 | "4 1 35 0 0 0 0 1 0 \n", 153 | "5 0 35 1 0 1 0 1 1 \n", 154 | "6 0 28 1 0 1 1 0 1 " 155 | ] 156 | }, 157 | "metadata": {}, 158 | "output_type": "display_data" 159 | } 160 | ], 161 | "source": [ 162 | "# Import processed dataset (generated from Logistic_Regression_Assumptions.ipynb)\n", 163 | "df_titanic <- read.csv(file = 'data/train_processed.csv')\n", 164 | "df_titanic <- df_titanic[ , -which(names(df_titanic) %in% c(\"Fare\"))]\n", 165 | "head(df_titanic)" 166 | ] 167 | }, 168 | { 169 | "cell_type": "markdown", 170 | "metadata": {}, 171 | "source": [ 172 | "### 1. Box-Tidwell Test with `car` library's `boxTidwell`\n", 173 | "- We can run Box-Tidwell test directly using the boxTidwell function within the `car` package" 174 | ] 175 | }, 176 | { 177 | "cell_type": "code", 178 | "execution_count": 11, 179 | "metadata": { 180 | "scrolled": true 181 | }, 182 | "outputs": [ 183 | { 184 | "data": { 185 | "text/plain": [ 186 | " MLE of lambda Score Statistic (z) Pr(>|z|) \n", 187 | " -0.30553 2.4529 0.01417 *\n", 188 | "---\n", 189 | "Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n", 190 | "\n", 191 | "iterations = 7 " 192 | ] 193 | }, 194 | "metadata": {}, 195 | "output_type": "display_data" 196 | } 197 | ], 198 | "source": [ 199 | "# Running Box-Tidwell test with `boxTidwell`\n", 200 | "boxTidwell(formula = Survived ~ Age, \n", 201 | " other.x = ~ TravelAlone + Pclass_2 + Pclass_3 + Embarked_Q + Embarked_S + Sex_male, \n", 202 | " data = df_titanic)" 203 | ] 204 | }, 205 | { 206 | "cell_type": "markdown", 207 | "metadata": {}, 208 | "source": [ 209 | "- p-value = 0.01417, which is <0.05 (meaning that it is statistically significant)\n", 210 | "- This means that there is non-linearity in the Age feature, and the assumption has been violated\n", 211 | "- We can resolve this by including a polynomial term (e.g. Age^2) to account for the non-linearity" 212 | ] 213 | }, 214 | { 215 | "cell_type": "markdown", 216 | "metadata": {}, 217 | "source": [ 218 | "___\n", 219 | "### 2. Box-Tidwell Test (add interaction terms directly)" 220 | ] 221 | }, 222 | { 223 | "cell_type": "code", 224 | "execution_count": 16, 225 | "metadata": { 226 | "scrolled": true 227 | }, 228 | "outputs": [ 229 | { 230 | "data": { 231 | "text/plain": [ 232 | "\n", 233 | "Call:\n", 234 | "glm(formula = Survived ~ Age + (Age:log(Age)) + TravelAlone + \n", 235 | " Pclass_2 + Pclass_3 + Embarked_Q + Embarked_S + Sex_male, \n", 236 | " family = binomial(link = \"logit\"), data = df_titanic)\n", 237 | "\n", 238 | "Deviance Residuals: \n", 239 | " Min 1Q Median 3Q Max \n", 240 | "-2.7718 -0.6597 -0.3871 0.6388 2.4610 \n", 241 | "\n", 242 | "Coefficients:\n", 243 | " Estimate Std. Error z value Pr(>|z|) \n", 244 | "(Intercept) 4.67512 0.54968 8.505 < 2e-16 ***\n", 245 | "Age -0.18594 0.06988 -2.661 0.007791 ** \n", 246 | "TravelAlone 0.21111 0.19919 1.060 0.289224 \n", 247 | "Pclass_2 -0.96542 0.27101 -3.562 0.000368 ***\n", 248 | "Pclass_3 -2.34673 0.25961 -9.039 < 2e-16 ***\n", 249 | "Embarked_Q 0.01839 0.37310 0.049 0.960678 \n", 250 | "Embarked_S -0.53215 0.23650 -2.250 0.024444 * \n", 251 | "Sex_male -2.62753 0.20036 -13.114 < 2e-16 ***\n", 252 | "Age:log(Age) 0.03508 0.01599 2.194 0.028232 * \n", 253 | "---\n", 254 | "Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n", 255 | "\n", 256 | "(Dispersion parameter for binomial family taken to be 1)\n", 257 | "\n", 258 | " Null deviance: 1171.07 on 875 degrees of freedom\n", 259 | "Residual deviance: 779.05 on 867 degrees of freedom\n", 260 | "AIC: 797.05\n", 261 | "\n", 262 | "Number of Fisher Scoring iterations: 5\n" 263 | ] 264 | }, 265 | "metadata": {}, 266 | "output_type": "display_data" 267 | } 268 | ], 269 | "source": [ 270 | "lreg <- glm(Survived ~ Age + (Age:log(Age)) + TravelAlone + Pclass_2 + Pclass_3 + Embarked_Q + Embarked_S + Sex_male, \n", 271 | " data=df_titanic, \n", 272 | " family=binomial(link=\"logit\"))\n", 273 | "logodds <- lreg$linear.predictors\n", 274 | "summary(lreg)" 275 | ] 276 | }, 277 | { 278 | "cell_type": "code", 279 | "execution_count": 17, 280 | "metadata": {}, 281 | "outputs": [ 282 | { 283 | "data": { 284 | "image/png": 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285 | "text/plain": [ 286 | "plot without title" 287 | ] 288 | }, 289 | "metadata": { 290 | "image/png": { 291 | "height": 420, 292 | "width": 420 293 | } 294 | }, 295 | "output_type": "display_data" 296 | } 297 | ], 298 | "source": [ 299 | "# Plot the log odds against the x (independent) predictor variable\n", 300 | "plot.dat <- data.frame(logodds = logodds, age = df_titanic$Age)\n", 301 | "ggplot(plot.dat, aes(x=age, y=logodds)) + geom_point()" 302 | ] 303 | }, 304 | { 305 | "cell_type": "markdown", 306 | "metadata": {}, 307 | "source": [ 308 | "___" 309 | ] 310 | }, 311 | { 312 | "cell_type": "code", 313 | "execution_count": null, 314 | "metadata": {}, 315 | "outputs": [], 316 | "source": [ 317 | "# # Reference: https://stackoverflow.com/questions/27278745/can-the-boxtidwell-function-handle-binary-outcome-variables\n", 318 | "# x<-df_titanic$Age\n", 319 | "# y<-df_titanic$Survived\n", 320 | "\n", 321 | "# #FIT IS DONE USING THE glm FUNCTION\n", 322 | "# m1res <- glm(y ~ x,family=binomial(link = \"logit\"))\n", 323 | "# coeff1<- coefficients(summary(m1res))\n", 324 | "# lnx<-x*log(x)\n", 325 | "# m2res <- glm(y ~ x+lnx ,family=binomial(link = \"logit\"))\n", 326 | "# coeff2<- coefficients(summary(m2res))\n", 327 | "# alpha0<-1.0\n", 328 | "# pvalue<-coeff2[3,4]\n", 329 | "\n", 330 | "# pvalue\n", 331 | "# beta1<-coeff1[2,1]\n", 332 | "# beta2<-coeff2[3,1]\n", 333 | "# iter<-0\n", 334 | "# err<-1\n", 335 | "\n", 336 | "# while (pvalue<0.1) {\n", 337 | "# alpha <-(beta2/beta1)+alpha0 \n", 338 | "# err<-abs(alpha-alpha0)\n", 339 | "# alpha0<-alpha\n", 340 | "# mx<-x^alpha\n", 341 | "# m1res <- glm(y ~ mx,family=binomial(link = \"logit\"))\n", 342 | "# coeff1<- coefficients(summary(m1res))\n", 343 | "# mlnx<-mx*log(x)\n", 344 | "# m2res <- glm(y ~ mx+mlnx ,family=binomial(link = \"logit\"))\n", 345 | "# coeff2<- coefficients(summary(m2res))\n", 346 | "# pvalue<-coeff2[3,4]\n", 347 | "# beta1<-coeff1[2,1]\n", 348 | "# beta2<-coeff2[3,1]\n", 349 | "# iter<- iter+1\n", 350 | "# }\n", 351 | "\n", 352 | "# # PRINT THE POWER TO CONSOLE\n", 353 | "# alpha" 354 | ] 355 | }, 356 | { 357 | "cell_type": "code", 358 | "execution_count": 41, 359 | "metadata": { 360 | "scrolled": true 361 | }, 362 | "outputs": [ 363 | { 364 | "data": { 365 | "text/html": [ 366 | "\n", 367 | "\n", 368 | "\n", 369 | "\t\n", 370 | "\t\n", 371 | "\n", 372 | "\n", 373 | "\t\n", 374 | "\t\n", 375 | "\t\n", 376 | "\t\n", 377 | "\t\n", 378 | "\t\n", 379 | "\t\n", 380 | "\t\n", 381 | "\t\n", 382 | "\t\n", 383 | "\t\n", 384 | "\t\n", 385 | "\t\n", 386 | "\t\n", 387 | "\t\n", 388 | "\t\n", 389 | "\t\n", 390 | "\t\n", 391 | "\t\n", 392 | "\t\n", 393 | "\t\n", 394 | "\t\n", 395 | "\t\n", 396 | "\t\n", 397 | "\t\n", 398 | "\t\n", 399 | "\t\n", 400 | "\t\n", 401 | "\t\n", 402 | "\t\n", 403 | "\t\n", 404 | "\t\n", 405 | "\t\n", 406 | "\t\n", 407 | "\t\n", 408 | "\t\n", 409 | "\t\n", 410 | "\t\n", 411 | "\t\n", 412 | "\t\n", 413 | "\t\n", 414 | "\t\n", 415 | "\t\n", 416 | "\t\n", 417 | "\t\n", 418 | "\t\n", 419 | "\t\n", 420 | "\t\n", 421 | "\t\n", 422 | "\t\n", 423 | "\t\n", 424 | "\t\n", 425 | "\t\n", 426 | "\t\n", 427 | "\t\n", 428 | "\t\n", 429 | "\t\n", 430 | "\t\n", 431 | "\t\n", 432 | "\t\n", 433 | "\t\n", 434 | "\n", 435 | "
A data.frame: 102 × 6
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gov.administrators13.111235111.1668.81113prof
general.managers12.2625879 4.0269.11130prof
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physicists15.6411030 5.1377.62113prof
biologists15.09 825825.6572.62133prof
architects15.4414163 2.6978.12141prof
civil.engineers14.5211377 1.0373.12143prof
mining.engineers14.6411023 0.9468.82153prof
surveyors12.39 5902 1.9162.02161prof
draughtsmen12.30 7059 7.8360.02163prof
computer.programers13.83 842515.3353.82183prof
economists14.44 804957.3162.22311prof
psychologists14.36 740548.2874.92315prof
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ministers14.50 4686 4.1472.82511prof
university.teachers15.971248019.5984.62711prof
primary.school.teachers13.62 564883.7859.62731prof
secondary.school.teachers15.08 803446.8066.12733prof
physicians15.962530810.5687.23111prof
veterinarians15.9414558 4.3266.73115prof
osteopaths.chiropractors14.7117498 6.9168.43117prof
nurses12.46 461496.1264.73131prof
nursing.aides 9.45 348576.1434.93135bc
physio.therapsts13.62 509282.6672.13137prof
pharmacists15.211043224.7169.33151prof
.....................
canners 7.42 189072.2423.28221bc
textile.weavers 6.69 444331.3633.38267bc
textile.labourers 6.74 348539.4828.88278bc
tool.die.makers10.09 8043 1.5042.58311bc
machinists 8.81 6686 4.2844.28313bc
sheet.metal.workers 8.40 6565 2.3035.98333bc
welders 7.92 6477 5.1741.88335bc
auto.workers 8.43 581113.6235.98513bc
aircraft.workers 8.78 6573 5.7843.78515bc
electronic.workers 8.76 394274.5450.88534bc
radio.tv.repairmen10.29 5449 2.9237.28537bc
sewing.mach.operators 6.38 284790.6728.28563bc
auto.repairmen 8.10 5795 0.8138.18581bc
aircraft.repairmen10.10 7716 0.7850.38582bc
railway.sectionmen 6.67 4696 0.0027.38715bc
electrical.linemen 9.05 8316 1.3440.98731bc
electricians 9.93 7147 0.9950.28733bc
construction.foremen 8.24 8880 0.6551.18780bc
carpenters 6.92 5299 0.5638.98781bc
masons 6.60 5959 0.5236.28782bc
house.painters 7.81 4549 2.4629.98785bc
plumbers 8.33 6928 0.6142.98791bc
construction.labourers 7.52 3910 1.0926.58798bc
pilots12.2714032 0.5866.19111prof
train.engineers 8.49 8845 0.0048.99131bc
bus.drivers 7.58 5562 9.4735.99171bc
taxi.drivers 7.93 4224 3.5925.19173bc
longshoremen 8.37 4753 0.0026.19313bc
typesetters10.00 646213.5842.29511bc
bookbinders 8.55 361770.8735.29517bc
\n" 436 | ], 437 | "text/latex": [ 438 | "A data.frame: 102 × 6\n", 439 | "\\begin{tabular}{r|llllll}\n", 440 | " & education & income & women & prestige & census & type\\\\\n", 441 | " & & & & & & \\\\\n", 442 | "\\hline\n", 443 | "\tgov.administrators & 13.11 & 12351 & 11.16 & 68.8 & 1113 & prof\\\\\n", 444 | "\tgeneral.managers & 12.26 & 25879 & 4.02 & 69.1 & 1130 & prof\\\\\n", 445 | "\taccountants & 12.77 & 9271 & 15.70 & 63.4 & 1171 & prof\\\\\n", 446 | "\tpurchasing.officers & 11.42 & 8865 & 9.11 & 56.8 & 1175 & prof\\\\\n", 447 | "\tchemists & 14.62 & 8403 & 11.68 & 73.5 & 2111 & prof\\\\\n", 448 | "\tphysicists & 15.64 & 11030 & 5.13 & 77.6 & 2113 & prof\\\\\n", 449 | "\tbiologists & 15.09 & 8258 & 25.65 & 72.6 & 2133 & prof\\\\\n", 450 | "\tarchitects & 15.44 & 14163 & 2.69 & 78.1 & 2141 & prof\\\\\n", 451 | "\tcivil.engineers & 14.52 & 11377 & 1.03 & 73.1 & 2143 & prof\\\\\n", 452 | "\tmining.engineers & 14.64 & 11023 & 0.94 & 68.8 & 2153 & prof\\\\\n", 453 | "\tsurveyors & 12.39 & 5902 & 1.91 & 62.0 & 2161 & prof\\\\\n", 454 | "\tdraughtsmen & 12.30 & 7059 & 7.83 & 60.0 & 2163 & prof\\\\\n", 455 | "\tcomputer.programers & 13.83 & 8425 & 15.33 & 53.8 & 2183 & prof\\\\\n", 456 | "\teconomists & 14.44 & 8049 & 57.31 & 62.2 & 2311 & prof\\\\\n", 457 | "\tpsychologists & 14.36 & 7405 & 48.28 & 74.9 & 2315 & prof\\\\\n", 458 | "\tsocial.workers & 14.21 & 6336 & 54.77 & 55.1 & 2331 & prof\\\\\n", 459 | "\tlawyers & 15.77 & 19263 & 5.13 & 82.3 & 2343 & prof\\\\\n", 460 | "\tlibrarians & 14.15 & 6112 & 77.10 & 58.1 & 2351 & prof\\\\\n", 461 | "\tvocational.counsellors & 15.22 & 9593 & 34.89 & 58.3 & 2391 & prof\\\\\n", 462 | "\tministers & 14.50 & 4686 & 4.14 & 72.8 & 2511 & prof\\\\\n", 463 | "\tuniversity.teachers & 15.97 & 12480 & 19.59 & 84.6 & 2711 & prof\\\\\n", 464 | "\tprimary.school.teachers & 13.62 & 5648 & 83.78 & 59.6 & 2731 & prof\\\\\n", 465 | "\tsecondary.school.teachers & 15.08 & 8034 & 46.80 & 66.1 & 2733 & prof\\\\\n", 466 | "\tphysicians & 15.96 & 25308 & 10.56 & 87.2 & 3111 & prof\\\\\n", 467 | "\tveterinarians & 15.94 & 14558 & 4.32 & 66.7 & 3115 & prof\\\\\n", 468 | "\tosteopaths.chiropractors & 14.71 & 17498 & 6.91 & 68.4 & 3117 & prof\\\\\n", 469 | "\tnurses & 12.46 & 4614 & 96.12 & 64.7 & 3131 & prof\\\\\n", 470 | "\tnursing.aides & 9.45 & 3485 & 76.14 & 34.9 & 3135 & bc \\\\\n", 471 | "\tphysio.therapsts & 13.62 & 5092 & 82.66 & 72.1 & 3137 & prof\\\\\n", 472 | "\tpharmacists & 15.21 & 10432 & 24.71 & 69.3 & 3151 & prof\\\\\n", 473 | "\t... & ... & ... & ... & ... & ... & ...\\\\\n", 474 | "\tcanners & 7.42 & 1890 & 72.24 & 23.2 & 8221 & bc \\\\\n", 475 | "\ttextile.weavers & 6.69 & 4443 & 31.36 & 33.3 & 8267 & bc \\\\\n", 476 | "\ttextile.labourers & 6.74 & 3485 & 39.48 & 28.8 & 8278 & bc \\\\\n", 477 | "\ttool.die.makers & 10.09 & 8043 & 1.50 & 42.5 & 8311 & bc \\\\\n", 478 | "\tmachinists & 8.81 & 6686 & 4.28 & 44.2 & 8313 & bc \\\\\n", 479 | "\tsheet.metal.workers & 8.40 & 6565 & 2.30 & 35.9 & 8333 & bc \\\\\n", 480 | "\twelders & 7.92 & 6477 & 5.17 & 41.8 & 8335 & bc \\\\\n", 481 | "\tauto.workers & 8.43 & 5811 & 13.62 & 35.9 & 8513 & bc \\\\\n", 482 | "\taircraft.workers & 8.78 & 6573 & 5.78 & 43.7 & 8515 & bc \\\\\n", 483 | "\telectronic.workers & 8.76 & 3942 & 74.54 & 50.8 & 8534 & bc \\\\\n", 484 | "\tradio.tv.repairmen & 10.29 & 5449 & 2.92 & 37.2 & 8537 & bc \\\\\n", 485 | "\tsewing.mach.operators & 6.38 & 2847 & 90.67 & 28.2 & 8563 & bc \\\\\n", 486 | "\tauto.repairmen & 8.10 & 5795 & 0.81 & 38.1 & 8581 & bc \\\\\n", 487 | "\taircraft.repairmen & 10.10 & 7716 & 0.78 & 50.3 & 8582 & bc \\\\\n", 488 | "\trailway.sectionmen & 6.67 & 4696 & 0.00 & 27.3 & 8715 & bc \\\\\n", 489 | "\telectrical.linemen & 9.05 & 8316 & 1.34 & 40.9 & 8731 & bc \\\\\n", 490 | "\telectricians & 9.93 & 7147 & 0.99 & 50.2 & 8733 & bc \\\\\n", 491 | "\tconstruction.foremen & 8.24 & 8880 & 0.65 & 51.1 & 8780 & bc \\\\\n", 492 | "\tcarpenters & 6.92 & 5299 & 0.56 & 38.9 & 8781 & bc \\\\\n", 493 | "\tmasons & 6.60 & 5959 & 0.52 & 36.2 & 8782 & bc \\\\\n", 494 | "\thouse.painters & 7.81 & 4549 & 2.46 & 29.9 & 8785 & bc \\\\\n", 495 | "\tplumbers & 8.33 & 6928 & 0.61 & 42.9 & 8791 & bc \\\\\n", 496 | "\tconstruction.labourers & 7.52 & 3910 & 1.09 & 26.5 & 8798 & bc \\\\\n", 497 | "\tpilots & 12.27 & 14032 & 0.58 & 66.1 & 9111 & prof\\\\\n", 498 | "\ttrain.engineers & 8.49 & 8845 & 0.00 & 48.9 & 9131 & bc \\\\\n", 499 | "\tbus.drivers & 7.58 & 5562 & 9.47 & 35.9 & 9171 & bc \\\\\n", 500 | "\ttaxi.drivers & 7.93 & 4224 & 3.59 & 25.1 & 9173 & bc \\\\\n", 501 | "\tlongshoremen & 8.37 & 4753 & 0.00 & 26.1 & 9313 & bc \\\\\n", 502 | "\ttypesetters & 10.00 & 6462 & 13.58 & 42.2 & 9511 & bc \\\\\n", 503 | "\tbookbinders & 8.55 & 3617 & 70.87 & 35.2 & 9517 & bc \\\\\n", 504 | "\\end{tabular}\n" 505 | ], 506 | "text/markdown": [ 507 | "\n", 508 | "A data.frame: 102 × 6\n", 509 | "\n", 510 | "| | education <dbl> | income <int> | women <dbl> | prestige <dbl> | census <int> | type <fct> |\n", 511 | "|---|---|---|---|---|---|---|\n", 512 | "| gov.administrators | 13.11 | 12351 | 11.16 | 68.8 | 1113 | prof |\n", 513 | "| general.managers | 12.26 | 25879 | 4.02 | 69.1 | 1130 | prof |\n", 514 | "| accountants | 12.77 | 9271 | 15.70 | 63.4 | 1171 | prof |\n", 515 | "| purchasing.officers | 11.42 | 8865 | 9.11 | 56.8 | 1175 | prof |\n", 516 | "| chemists | 14.62 | 8403 | 11.68 | 73.5 | 2111 | prof |\n", 517 | "| physicists | 15.64 | 11030 | 5.13 | 77.6 | 2113 | prof |\n", 518 | "| biologists | 15.09 | 8258 | 25.65 | 72.6 | 2133 | prof |\n", 519 | "| architects | 15.44 | 14163 | 2.69 | 78.1 | 2141 | prof |\n", 520 | "| civil.engineers | 14.52 | 11377 | 1.03 | 73.1 | 2143 | prof |\n", 521 | "| mining.engineers | 14.64 | 11023 | 0.94 | 68.8 | 2153 | prof |\n", 522 | "| surveyors | 12.39 | 5902 | 1.91 | 62.0 | 2161 | prof |\n", 523 | "| draughtsmen | 12.30 | 7059 | 7.83 | 60.0 | 2163 | prof |\n", 524 | "| computer.programers | 13.83 | 8425 | 15.33 | 53.8 | 2183 | prof |\n", 525 | "| economists | 14.44 | 8049 | 57.31 | 62.2 | 2311 | prof |\n", 526 | "| psychologists | 14.36 | 7405 | 48.28 | 74.9 | 2315 | prof |\n", 527 | "| social.workers | 14.21 | 6336 | 54.77 | 55.1 | 2331 | prof |\n", 528 | "| lawyers | 15.77 | 19263 | 5.13 | 82.3 | 2343 | prof |\n", 529 | "| librarians | 14.15 | 6112 | 77.10 | 58.1 | 2351 | prof |\n", 530 | "| vocational.counsellors | 15.22 | 9593 | 34.89 | 58.3 | 2391 | prof |\n", 531 | "| ministers | 14.50 | 4686 | 4.14 | 72.8 | 2511 | prof |\n", 532 | "| university.teachers | 15.97 | 12480 | 19.59 | 84.6 | 2711 | prof |\n", 533 | "| primary.school.teachers | 13.62 | 5648 | 83.78 | 59.6 | 2731 | prof |\n", 534 | "| secondary.school.teachers | 15.08 | 8034 | 46.80 | 66.1 | 2733 | prof |\n", 535 | "| physicians | 15.96 | 25308 | 10.56 | 87.2 | 3111 | prof |\n", 536 | "| veterinarians | 15.94 | 14558 | 4.32 | 66.7 | 3115 | prof |\n", 537 | "| osteopaths.chiropractors | 14.71 | 17498 | 6.91 | 68.4 | 3117 | prof |\n", 538 | "| nurses | 12.46 | 4614 | 96.12 | 64.7 | 3131 | prof |\n", 539 | "| nursing.aides | 9.45 | 3485 | 76.14 | 34.9 | 3135 | bc |\n", 540 | "| physio.therapsts | 13.62 | 5092 | 82.66 | 72.1 | 3137 | prof |\n", 541 | "| pharmacists | 15.21 | 10432 | 24.71 | 69.3 | 3151 | prof |\n", 542 | "| ... | ... | ... | ... | ... | ... | ... |\n", 543 | "| canners | 7.42 | 1890 | 72.24 | 23.2 | 8221 | bc |\n", 544 | "| textile.weavers | 6.69 | 4443 | 31.36 | 33.3 | 8267 | bc |\n", 545 | "| textile.labourers | 6.74 | 3485 | 39.48 | 28.8 | 8278 | bc |\n", 546 | "| tool.die.makers | 10.09 | 8043 | 1.50 | 42.5 | 8311 | bc |\n", 547 | "| machinists | 8.81 | 6686 | 4.28 | 44.2 | 8313 | bc |\n", 548 | "| sheet.metal.workers | 8.40 | 6565 | 2.30 | 35.9 | 8333 | bc |\n", 549 | "| welders | 7.92 | 6477 | 5.17 | 41.8 | 8335 | bc |\n", 550 | "| auto.workers | 8.43 | 5811 | 13.62 | 35.9 | 8513 | bc |\n", 551 | "| aircraft.workers | 8.78 | 6573 | 5.78 | 43.7 | 8515 | bc |\n", 552 | "| electronic.workers | 8.76 | 3942 | 74.54 | 50.8 | 8534 | bc |\n", 553 | "| radio.tv.repairmen | 10.29 | 5449 | 2.92 | 37.2 | 8537 | bc |\n", 554 | "| sewing.mach.operators | 6.38 | 2847 | 90.67 | 28.2 | 8563 | bc |\n", 555 | "| auto.repairmen | 8.10 | 5795 | 0.81 | 38.1 | 8581 | bc |\n", 556 | "| aircraft.repairmen | 10.10 | 7716 | 0.78 | 50.3 | 8582 | bc |\n", 557 | "| railway.sectionmen | 6.67 | 4696 | 0.00 | 27.3 | 8715 | bc |\n", 558 | "| electrical.linemen | 9.05 | 8316 | 1.34 | 40.9 | 8731 | bc |\n", 559 | "| electricians | 9.93 | 7147 | 0.99 | 50.2 | 8733 | bc |\n", 560 | "| construction.foremen | 8.24 | 8880 | 0.65 | 51.1 | 8780 | bc |\n", 561 | "| carpenters | 6.92 | 5299 | 0.56 | 38.9 | 8781 | bc |\n", 562 | "| masons | 6.60 | 5959 | 0.52 | 36.2 | 8782 | bc |\n", 563 | "| house.painters | 7.81 | 4549 | 2.46 | 29.9 | 8785 | bc |\n", 564 | "| plumbers | 8.33 | 6928 | 0.61 | 42.9 | 8791 | bc |\n", 565 | "| construction.labourers | 7.52 | 3910 | 1.09 | 26.5 | 8798 | bc |\n", 566 | "| pilots | 12.27 | 14032 | 0.58 | 66.1 | 9111 | prof |\n", 567 | "| train.engineers | 8.49 | 8845 | 0.00 | 48.9 | 9131 | bc |\n", 568 | "| bus.drivers | 7.58 | 5562 | 9.47 | 35.9 | 9171 | bc |\n", 569 | "| taxi.drivers | 7.93 | 4224 | 3.59 | 25.1 | 9173 | bc |\n", 570 | "| longshoremen | 8.37 | 4753 | 0.00 | 26.1 | 9313 | bc |\n", 571 | "| typesetters | 10.00 | 6462 | 13.58 | 42.2 | 9511 | bc |\n", 572 | "| bookbinders | 8.55 | 3617 | 70.87 | 35.2 | 9517 | bc |\n", 573 | "\n" 574 | ], 575 | "text/plain": [ 576 | " education income women prestige census type\n", 577 | "gov.administrators 13.11 12351 11.16 68.8 1113 prof\n", 578 | "general.managers 12.26 25879 4.02 69.1 1130 prof\n", 579 | "accountants 12.77 9271 15.70 63.4 1171 prof\n", 580 | "purchasing.officers 11.42 8865 9.11 56.8 1175 prof\n", 581 | "chemists 14.62 8403 11.68 73.5 2111 prof\n", 582 | "physicists 15.64 11030 5.13 77.6 2113 prof\n", 583 | "biologists 15.09 8258 25.65 72.6 2133 prof\n", 584 | "architects 15.44 14163 2.69 78.1 2141 prof\n", 585 | "civil.engineers 14.52 11377 1.03 73.1 2143 prof\n", 586 | "mining.engineers 14.64 11023 0.94 68.8 2153 prof\n", 587 | "surveyors 12.39 5902 1.91 62.0 2161 prof\n", 588 | "draughtsmen 12.30 7059 7.83 60.0 2163 prof\n", 589 | "computer.programers 13.83 8425 15.33 53.8 2183 prof\n", 590 | "economists 14.44 8049 57.31 62.2 2311 prof\n", 591 | "psychologists 14.36 7405 48.28 74.9 2315 prof\n", 592 | "social.workers 14.21 6336 54.77 55.1 2331 prof\n", 593 | "lawyers 15.77 19263 5.13 82.3 2343 prof\n", 594 | "librarians 14.15 6112 77.10 58.1 2351 prof\n", 595 | "vocational.counsellors 15.22 9593 34.89 58.3 2391 prof\n", 596 | "ministers 14.50 4686 4.14 72.8 2511 prof\n", 597 | "university.teachers 15.97 12480 19.59 84.6 2711 prof\n", 598 | "primary.school.teachers 13.62 5648 83.78 59.6 2731 prof\n", 599 | "secondary.school.teachers 15.08 8034 46.80 66.1 2733 prof\n", 600 | "physicians 15.96 25308 10.56 87.2 3111 prof\n", 601 | "veterinarians 15.94 14558 4.32 66.7 3115 prof\n", 602 | "osteopaths.chiropractors 14.71 17498 6.91 68.4 3117 prof\n", 603 | "nurses 12.46 4614 96.12 64.7 3131 prof\n", 604 | "nursing.aides 9.45 3485 76.14 34.9 3135 bc \n", 605 | "physio.therapsts 13.62 5092 82.66 72.1 3137 prof\n", 606 | "pharmacists 15.21 10432 24.71 69.3 3151 prof\n", 607 | "... ... ... ... ... ... ... \n", 608 | "canners 7.42 1890 72.24 23.2 8221 bc \n", 609 | "textile.weavers 6.69 4443 31.36 33.3 8267 bc \n", 610 | "textile.labourers 6.74 3485 39.48 28.8 8278 bc \n", 611 | "tool.die.makers 10.09 8043 1.50 42.5 8311 bc \n", 612 | "machinists 8.81 6686 4.28 44.2 8313 bc \n", 613 | "sheet.metal.workers 8.40 6565 2.30 35.9 8333 bc \n", 614 | "welders 7.92 6477 5.17 41.8 8335 bc \n", 615 | "auto.workers 8.43 5811 13.62 35.9 8513 bc \n", 616 | "aircraft.workers 8.78 6573 5.78 43.7 8515 bc \n", 617 | "electronic.workers 8.76 3942 74.54 50.8 8534 bc \n", 618 | "radio.tv.repairmen 10.29 5449 2.92 37.2 8537 bc \n", 619 | "sewing.mach.operators 6.38 2847 90.67 28.2 8563 bc \n", 620 | "auto.repairmen 8.10 5795 0.81 38.1 8581 bc \n", 621 | "aircraft.repairmen 10.10 7716 0.78 50.3 8582 bc \n", 622 | "railway.sectionmen 6.67 4696 0.00 27.3 8715 bc \n", 623 | "electrical.linemen 9.05 8316 1.34 40.9 8731 bc \n", 624 | "electricians 9.93 7147 0.99 50.2 8733 bc \n", 625 | "construction.foremen 8.24 8880 0.65 51.1 8780 bc \n", 626 | "carpenters 6.92 5299 0.56 38.9 8781 bc \n", 627 | "masons 6.60 5959 0.52 36.2 8782 bc \n", 628 | "house.painters 7.81 4549 2.46 29.9 8785 bc \n", 629 | "plumbers 8.33 6928 0.61 42.9 8791 bc \n", 630 | "construction.labourers 7.52 3910 1.09 26.5 8798 bc \n", 631 | "pilots 12.27 14032 0.58 66.1 9111 prof\n", 632 | "train.engineers 8.49 8845 0.00 48.9 9131 bc \n", 633 | "bus.drivers 7.58 5562 9.47 35.9 9171 bc \n", 634 | "taxi.drivers 7.93 4224 3.59 25.1 9173 bc \n", 635 | "longshoremen 8.37 4753 0.00 26.1 9313 bc \n", 636 | "typesetters 10.00 6462 13.58 42.2 9511 bc \n", 637 | "bookbinders 8.55 3617 70.87 35.2 9517 bc " 638 | ] 639 | }, 640 | "metadata": {}, 641 | "output_type": "display_data" 642 | } 643 | ], 644 | "source": [ 645 | "# Standard example for Box-Tidwell (on Prestige dataset)\n", 646 | "# Prestige" 647 | ] 648 | }, 649 | { 650 | "cell_type": "code", 651 | "execution_count": 46, 652 | "metadata": {}, 653 | "outputs": [ 654 | { 655 | "data": { 656 | "text/plain": [ 657 | " MLE of lambda Score Statistic (z) Pr(>|z|) \n", 658 | "income -0.34763 -4.4824 7.381e-06 ***\n", 659 | "education 1.25383 0.2170 0.8282 \n", 660 | "---\n", 661 | "Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n", 662 | "\n", 663 | "iterations = 8 " 664 | ] 665 | }, 666 | "metadata": {}, 667 | "output_type": "display_data" 668 | } 669 | ], 670 | "source": [ 671 | "# boxTidwell(prestige ~ income + education, ~ type + poly(women, 2), data=Prestige)" 672 | ] 673 | } 674 | ], 675 | "metadata": { 676 | "kernelspec": { 677 | "display_name": "R", 678 | "language": "R", 679 | "name": "ir" 680 | }, 681 | "language_info": { 682 | "codemirror_mode": "r", 683 | "file_extension": ".r", 684 | "mimetype": "text/x-r-source", 685 | "name": "R", 686 | "pygments_lexer": "r", 687 | "version": "4.1.1" 688 | } 689 | }, 690 | "nbformat": 4, 691 | "nbformat_minor": 4 692 | } 693 | -------------------------------------------------------------------------------- /datasets/Insurance.csv: -------------------------------------------------------------------------------- 1 | age,sex,bmi,children,smoker,region,charges 2 | 19,female,27.9,0,yes,southwest,16884.924 3 | 18,male,33.77,1,no,southeast,1725.5523 4 | 28,male,33,3,no,southeast,4449.462 5 | 33,male,22.705,0,no,northwest,21984.47061 6 | 32,male,28.88,0,no,northwest,3866.8552 7 | 31,female,25.74,0,no,southeast,3756.6216 8 | 46,female,33.44,1,no,southeast,8240.5896 9 | 37,female,27.74,3,no,northwest,7281.5056 10 | 37,male,29.83,2,no,northeast,6406.4107 11 | 60,female,25.84,0,no,northwest,28923.13692 12 | 25,male,26.22,0,no,northeast,2721.3208 13 | 62,female,26.29,0,yes,southeast,27808.7251 14 | 23,male,34.4,0,no,southwest,1826.843 15 | 56,female,39.82,0,no,southeast,11090.7178 16 | 27,male,42.13,0,yes,southeast,39611.7577 17 | 19,male,24.6,1,no,southwest,1837.237 18 | 52,female,30.78,1,no,northeast,10797.3362 19 | 23,male,23.845,0,no,northeast,2395.17155 20 | 56,male,40.3,0,no,southwest,10602.385 21 | 30,male,35.3,0,yes,southwest,36837.467 22 | 60,female,36.005,0,no,northeast,13228.84695 23 | 30,female,32.4,1,no,southwest,4149.736 24 | 18,male,34.1,0,no,southeast,1137.011 25 | 34,female,31.92,1,yes,northeast,37701.8768 26 | 37,male,28.025,2,no,northwest,6203.90175 27 | 59,female,27.72,3,no,southeast,14001.1338 28 | 63,female,23.085,0,no,northeast,14451.83515 29 | 55,female,32.775,2,no,northwest,12268.63225 30 | 23,male,17.385,1,no,northwest,2775.19215 31 | 31,male,36.3,2,yes,southwest,38711 32 | 22,male,35.6,0,yes,southwest,35585.576 33 | 18,female,26.315,0,no,northeast,2198.18985 34 | 19,female,28.6,5,no,southwest,4687.797 35 | 63,male,28.31,0,no,northwest,13770.0979 36 | 28,male,36.4,1,yes,southwest,51194.55914 37 | 19,male,20.425,0,no,northwest,1625.43375 38 | 62,female,32.965,3,no,northwest,15612.19335 39 | 26,male,20.8,0,no,southwest,2302.3 40 | 35,male,36.67,1,yes,northeast,39774.2763 41 | 60,male,39.9,0,yes,southwest,48173.361 42 | 24,female,26.6,0,no,northeast,3046.062 43 | 31,female,36.63,2,no,southeast,4949.7587 44 | 41,male,21.78,1,no,southeast,6272.4772 45 | 37,female,30.8,2,no,southeast,6313.759 46 | 38,male,37.05,1,no,northeast,6079.6715 47 | 55,male,37.3,0,no,southwest,20630.28351 48 | 18,female,38.665,2,no,northeast,3393.35635 49 | 28,female,34.77,0,no,northwest,3556.9223 50 | 60,female,24.53,0,no,southeast,12629.8967 51 | 36,male,35.2,1,yes,southeast,38709.176 52 | 18,female,35.625,0,no,northeast,2211.13075 53 | 21,female,33.63,2,no,northwest,3579.8287 54 | 48,male,28,1,yes,southwest,23568.272 55 | 36,male,34.43,0,yes,southeast,37742.5757 56 | 40,female,28.69,3,no,northwest,8059.6791 57 | 58,male,36.955,2,yes,northwest,47496.49445 58 | 58,female,31.825,2,no,northeast,13607.36875 59 | 18,male,31.68,2,yes,southeast,34303.1672 60 | 53,female,22.88,1,yes,southeast,23244.7902 61 | 34,female,37.335,2,no,northwest,5989.52365 62 | 43,male,27.36,3,no,northeast,8606.2174 63 | 25,male,33.66,4,no,southeast,4504.6624 64 | 64,male,24.7,1,no,northwest,30166.61817 65 | 28,female,25.935,1,no,northwest,4133.64165 66 | 20,female,22.42,0,yes,northwest,14711.7438 67 | 19,female,28.9,0,no,southwest,1743.214 68 | 61,female,39.1,2,no,southwest,14235.072 69 | 40,male,26.315,1,no,northwest,6389.37785 70 | 40,female,36.19,0,no,southeast,5920.1041 71 | 28,male,23.98,3,yes,southeast,17663.1442 72 | 27,female,24.75,0,yes,southeast,16577.7795 73 | 31,male,28.5,5,no,northeast,6799.458 74 | 53,female,28.1,3,no,southwest,11741.726 75 | 58,male,32.01,1,no,southeast,11946.6259 76 | 44,male,27.4,2,no,southwest,7726.854 77 | 57,male,34.01,0,no,northwest,11356.6609 78 | 29,female,29.59,1,no,southeast,3947.4131 79 | 21,male,35.53,0,no,southeast,1532.4697 80 | 22,female,39.805,0,no,northeast,2755.02095 81 | 41,female,32.965,0,no,northwest,6571.02435 82 | 31,male,26.885,1,no,northeast,4441.21315 83 | 45,female,38.285,0,no,northeast,7935.29115 84 | 22,male,37.62,1,yes,southeast,37165.1638 85 | 48,female,41.23,4,no,northwest,11033.6617 86 | 37,female,34.8,2,yes,southwest,39836.519 87 | 45,male,22.895,2,yes,northwest,21098.55405 88 | 57,female,31.16,0,yes,northwest,43578.9394 89 | 56,female,27.2,0,no,southwest,11073.176 90 | 46,female,27.74,0,no,northwest,8026.6666 91 | 55,female,26.98,0,no,northwest,11082.5772 92 | 21,female,39.49,0,no,southeast,2026.9741 93 | 53,female,24.795,1,no,northwest,10942.13205 94 | 59,male,29.83,3,yes,northeast,30184.9367 95 | 35,male,34.77,2,no,northwest,5729.0053 96 | 64,female,31.3,2,yes,southwest,47291.055 97 | 28,female,37.62,1,no,southeast,3766.8838 98 | 54,female,30.8,3,no,southwest,12105.32 99 | 55,male,38.28,0,no,southeast,10226.2842 100 | 56,male,19.95,0,yes,northeast,22412.6485 101 | 38,male,19.3,0,yes,southwest,15820.699 102 | 41,female,31.6,0,no,southwest,6186.127 103 | 30,male,25.46,0,no,northeast,3645.0894 104 | 18,female,30.115,0,no,northeast,21344.8467 105 | 61,female,29.92,3,yes,southeast,30942.1918 106 | 34,female,27.5,1,no,southwest,5003.853 107 | 20,male,28.025,1,yes,northwest,17560.37975 108 | 19,female,28.4,1,no,southwest,2331.519 109 | 26,male,30.875,2,no,northwest,3877.30425 110 | 29,male,27.94,0,no,southeast,2867.1196 111 | 63,male,35.09,0,yes,southeast,47055.5321 112 | 54,male,33.63,1,no,northwest,10825.2537 113 | 55,female,29.7,2,no,southwest,11881.358 114 | 37,male,30.8,0,no,southwest,4646.759 115 | 21,female,35.72,0,no,northwest,2404.7338 116 | 52,male,32.205,3,no,northeast,11488.31695 117 | 60,male,28.595,0,no,northeast,30259.99556 118 | 58,male,49.06,0,no,southeast,11381.3254 119 | 29,female,27.94,1,yes,southeast,19107.7796 120 | 49,female,27.17,0,no,southeast,8601.3293 121 | 37,female,23.37,2,no,northwest,6686.4313 122 | 44,male,37.1,2,no,southwest,7740.337 123 | 18,male,23.75,0,no,northeast,1705.6245 124 | 20,female,28.975,0,no,northwest,2257.47525 125 | 44,male,31.35,1,yes,northeast,39556.4945 126 | 47,female,33.915,3,no,northwest,10115.00885 127 | 26,female,28.785,0,no,northeast,3385.39915 128 | 19,female,28.3,0,yes,southwest,17081.08 129 | 52,female,37.4,0,no,southwest,9634.538 130 | 32,female,17.765,2,yes,northwest,32734.1863 131 | 38,male,34.7,2,no,southwest,6082.405 132 | 59,female,26.505,0,no,northeast,12815.44495 133 | 61,female,22.04,0,no,northeast,13616.3586 134 | 53,female,35.9,2,no,southwest,11163.568 135 | 19,male,25.555,0,no,northwest,1632.56445 136 | 20,female,28.785,0,no,northeast,2457.21115 137 | 22,female,28.05,0,no,southeast,2155.6815 138 | 19,male,34.1,0,no,southwest,1261.442 139 | 22,male,25.175,0,no,northwest,2045.68525 140 | 54,female,31.9,3,no,southeast,27322.73386 141 | 22,female,36,0,no,southwest,2166.732 142 | 34,male,22.42,2,no,northeast,27375.90478 143 | 26,male,32.49,1,no,northeast,3490.5491 144 | 34,male,25.3,2,yes,southeast,18972.495 145 | 29,male,29.735,2,no,northwest,18157.876 146 | 30,male,28.69,3,yes,northwest,20745.9891 147 | 29,female,38.83,3,no,southeast,5138.2567 148 | 46,male,30.495,3,yes,northwest,40720.55105 149 | 51,female,37.73,1,no,southeast,9877.6077 150 | 53,female,37.43,1,no,northwest,10959.6947 151 | 19,male,28.4,1,no,southwest,1842.519 152 | 35,male,24.13,1,no,northwest,5125.2157 153 | 48,male,29.7,0,no,southeast,7789.635 154 | 32,female,37.145,3,no,northeast,6334.34355 155 | 42,female,23.37,0,yes,northeast,19964.7463 156 | 40,female,25.46,1,no,northeast,7077.1894 157 | 44,male,39.52,0,no,northwest,6948.7008 158 | 48,male,24.42,0,yes,southeast,21223.6758 159 | 18,male,25.175,0,yes,northeast,15518.18025 160 | 30,male,35.53,0,yes,southeast,36950.2567 161 | 50,female,27.83,3,no,southeast,19749.38338 162 | 42,female,26.6,0,yes,northwest,21348.706 163 | 18,female,36.85,0,yes,southeast,36149.4835 164 | 54,male,39.6,1,no,southwest,10450.552 165 | 32,female,29.8,2,no,southwest,5152.134 166 | 37,male,29.64,0,no,northwest,5028.1466 167 | 47,male,28.215,4,no,northeast,10407.08585 168 | 20,female,37,5,no,southwest,4830.63 169 | 32,female,33.155,3,no,northwest,6128.79745 170 | 19,female,31.825,1,no,northwest,2719.27975 171 | 27,male,18.905,3,no,northeast,4827.90495 172 | 63,male,41.47,0,no,southeast,13405.3903 173 | 49,male,30.3,0,no,southwest,8116.68 174 | 18,male,15.96,0,no,northeast,1694.7964 175 | 35,female,34.8,1,no,southwest,5246.047 176 | 24,female,33.345,0,no,northwest,2855.43755 177 | 63,female,37.7,0,yes,southwest,48824.45 178 | 38,male,27.835,2,no,northwest,6455.86265 179 | 54,male,29.2,1,no,southwest,10436.096 180 | 46,female,28.9,2,no,southwest,8823.279 181 | 41,female,33.155,3,no,northeast,8538.28845 182 | 58,male,28.595,0,no,northwest,11735.87905 183 | 18,female,38.28,0,no,southeast,1631.8212 184 | 22,male,19.95,3,no,northeast,4005.4225 185 | 44,female,26.41,0,no,northwest,7419.4779 186 | 44,male,30.69,2,no,southeast,7731.4271 187 | 36,male,41.895,3,yes,northeast,43753.33705 188 | 26,female,29.92,2,no,southeast,3981.9768 189 | 30,female,30.9,3,no,southwest,5325.651 190 | 41,female,32.2,1,no,southwest,6775.961 191 | 29,female,32.11,2,no,northwest,4922.9159 192 | 61,male,31.57,0,no,southeast,12557.6053 193 | 36,female,26.2,0,no,southwest,4883.866 194 | 25,male,25.74,0,no,southeast,2137.6536 195 | 56,female,26.6,1,no,northwest,12044.342 196 | 18,male,34.43,0,no,southeast,1137.4697 197 | 19,male,30.59,0,no,northwest,1639.5631 198 | 39,female,32.8,0,no,southwest,5649.715 199 | 45,female,28.6,2,no,southeast,8516.829 200 | 51,female,18.05,0,no,northwest,9644.2525 201 | 64,female,39.33,0,no,northeast,14901.5167 202 | 19,female,32.11,0,no,northwest,2130.6759 203 | 48,female,32.23,1,no,southeast,8871.1517 204 | 60,female,24.035,0,no,northwest,13012.20865 205 | 27,female,36.08,0,yes,southeast,37133.8982 206 | 46,male,22.3,0,no,southwest,7147.105 207 | 28,female,28.88,1,no,northeast,4337.7352 208 | 59,male,26.4,0,no,southeast,11743.299 209 | 35,male,27.74,2,yes,northeast,20984.0936 210 | 63,female,31.8,0,no,southwest,13880.949 211 | 40,male,41.23,1,no,northeast,6610.1097 212 | 20,male,33,1,no,southwest,1980.07 213 | 40,male,30.875,4,no,northwest,8162.71625 214 | 24,male,28.5,2,no,northwest,3537.703 215 | 34,female,26.73,1,no,southeast,5002.7827 216 | 45,female,30.9,2,no,southwest,8520.026 217 | 41,female,37.1,2,no,southwest,7371.772 218 | 53,female,26.6,0,no,northwest,10355.641 219 | 27,male,23.1,0,no,southeast,2483.736 220 | 26,female,29.92,1,no,southeast,3392.9768 221 | 24,female,23.21,0,no,southeast,25081.76784 222 | 34,female,33.7,1,no,southwest,5012.471 223 | 53,female,33.25,0,no,northeast,10564.8845 224 | 32,male,30.8,3,no,southwest,5253.524 225 | 19,male,34.8,0,yes,southwest,34779.615 226 | 42,male,24.64,0,yes,southeast,19515.5416 227 | 55,male,33.88,3,no,southeast,11987.1682 228 | 28,male,38.06,0,no,southeast,2689.4954 229 | 58,female,41.91,0,no,southeast,24227.33724 230 | 41,female,31.635,1,no,northeast,7358.17565 231 | 47,male,25.46,2,no,northeast,9225.2564 232 | 42,female,36.195,1,no,northwest,7443.64305 233 | 59,female,27.83,3,no,southeast,14001.2867 234 | 19,female,17.8,0,no,southwest,1727.785 235 | 59,male,27.5,1,no,southwest,12333.828 236 | 39,male,24.51,2,no,northwest,6710.1919 237 | 40,female,22.22,2,yes,southeast,19444.2658 238 | 18,female,26.73,0,no,southeast,1615.7667 239 | 31,male,38.39,2,no,southeast,4463.2051 240 | 19,male,29.07,0,yes,northwest,17352.6803 241 | 44,male,38.06,1,no,southeast,7152.6714 242 | 23,female,36.67,2,yes,northeast,38511.6283 243 | 33,female,22.135,1,no,northeast,5354.07465 244 | 55,female,26.8,1,no,southwest,35160.13457 245 | 40,male,35.3,3,no,southwest,7196.867 246 | 63,female,27.74,0,yes,northeast,29523.1656 247 | 54,male,30.02,0,no,northwest,24476.47851 248 | 60,female,38.06,0,no,southeast,12648.7034 249 | 24,male,35.86,0,no,southeast,1986.9334 250 | 19,male,20.9,1,no,southwest,1832.094 251 | 29,male,28.975,1,no,northeast,4040.55825 252 | 18,male,17.29,2,yes,northeast,12829.4551 253 | 63,female,32.2,2,yes,southwest,47305.305 254 | 54,male,34.21,2,yes,southeast,44260.7499 255 | 27,male,30.3,3,no,southwest,4260.744 256 | 50,male,31.825,0,yes,northeast,41097.16175 257 | 55,female,25.365,3,no,northeast,13047.33235 258 | 56,male,33.63,0,yes,northwest,43921.1837 259 | 38,female,40.15,0,no,southeast,5400.9805 260 | 51,male,24.415,4,no,northwest,11520.09985 261 | 19,male,31.92,0,yes,northwest,33750.2918 262 | 58,female,25.2,0,no,southwest,11837.16 263 | 20,female,26.84,1,yes,southeast,17085.2676 264 | 52,male,24.32,3,yes,northeast,24869.8368 265 | 19,male,36.955,0,yes,northwest,36219.40545 266 | 53,female,38.06,3,no,southeast,20462.99766 267 | 46,male,42.35,3,yes,southeast,46151.1245 268 | 40,male,19.8,1,yes,southeast,17179.522 269 | 59,female,32.395,3,no,northeast,14590.63205 270 | 45,male,30.2,1,no,southwest,7441.053 271 | 49,male,25.84,1,no,northeast,9282.4806 272 | 18,male,29.37,1,no,southeast,1719.4363 273 | 50,male,34.2,2,yes,southwest,42856.838 274 | 41,male,37.05,2,no,northwest,7265.7025 275 | 50,male,27.455,1,no,northeast,9617.66245 276 | 25,male,27.55,0,no,northwest,2523.1695 277 | 47,female,26.6,2,no,northeast,9715.841 278 | 19,male,20.615,2,no,northwest,2803.69785 279 | 22,female,24.3,0,no,southwest,2150.469 280 | 59,male,31.79,2,no,southeast,12928.7911 281 | 51,female,21.56,1,no,southeast,9855.1314 282 | 40,female,28.12,1,yes,northeast,22331.5668 283 | 54,male,40.565,3,yes,northeast,48549.17835 284 | 30,male,27.645,1,no,northeast,4237.12655 285 | 55,female,32.395,1,no,northeast,11879.10405 286 | 52,female,31.2,0,no,southwest,9625.92 287 | 46,male,26.62,1,no,southeast,7742.1098 288 | 46,female,48.07,2,no,northeast,9432.9253 289 | 63,female,26.22,0,no,northwest,14256.1928 290 | 59,female,36.765,1,yes,northeast,47896.79135 291 | 52,male,26.4,3,no,southeast,25992.82104 292 | 28,female,33.4,0,no,southwest,3172.018 293 | 29,male,29.64,1,no,northeast,20277.80751 294 | 25,male,45.54,2,yes,southeast,42112.2356 295 | 22,female,28.82,0,no,southeast,2156.7518 296 | 25,male,26.8,3,no,southwest,3906.127 297 | 18,male,22.99,0,no,northeast,1704.5681 298 | 19,male,27.7,0,yes,southwest,16297.846 299 | 47,male,25.41,1,yes,southeast,21978.6769 300 | 31,male,34.39,3,yes,northwest,38746.3551 301 | 48,female,28.88,1,no,northwest,9249.4952 302 | 36,male,27.55,3,no,northeast,6746.7425 303 | 53,female,22.61,3,yes,northeast,24873.3849 304 | 56,female,37.51,2,no,southeast,12265.5069 305 | 28,female,33,2,no,southeast,4349.462 306 | 57,female,38,2,no,southwest,12646.207 307 | 29,male,33.345,2,no,northwest,19442.3535 308 | 28,female,27.5,2,no,southwest,20177.67113 309 | 30,female,33.33,1,no,southeast,4151.0287 310 | 58,male,34.865,0,no,northeast,11944.59435 311 | 41,female,33.06,2,no,northwest,7749.1564 312 | 50,male,26.6,0,no,southwest,8444.474 313 | 19,female,24.7,0,no,southwest,1737.376 314 | 43,male,35.97,3,yes,southeast,42124.5153 315 | 49,male,35.86,0,no,southeast,8124.4084 316 | 27,female,31.4,0,yes,southwest,34838.873 317 | 52,male,33.25,0,no,northeast,9722.7695 318 | 50,male,32.205,0,no,northwest,8835.26495 319 | 54,male,32.775,0,no,northeast,10435.06525 320 | 44,female,27.645,0,no,northwest,7421.19455 321 | 32,male,37.335,1,no,northeast,4667.60765 322 | 34,male,25.27,1,no,northwest,4894.7533 323 | 26,female,29.64,4,no,northeast,24671.66334 324 | 34,male,30.8,0,yes,southwest,35491.64 325 | 57,male,40.945,0,no,northeast,11566.30055 326 | 29,male,27.2,0,no,southwest,2866.091 327 | 40,male,34.105,1,no,northeast,6600.20595 328 | 27,female,23.21,1,no,southeast,3561.8889 329 | 45,male,36.48,2,yes,northwest,42760.5022 330 | 64,female,33.8,1,yes,southwest,47928.03 331 | 52,male,36.7,0,no,southwest,9144.565 332 | 61,female,36.385,1,yes,northeast,48517.56315 333 | 52,male,27.36,0,yes,northwest,24393.6224 334 | 61,female,31.16,0,no,northwest,13429.0354 335 | 56,female,28.785,0,no,northeast,11658.37915 336 | 43,female,35.72,2,no,northeast,19144.57652 337 | 64,male,34.5,0,no,southwest,13822.803 338 | 60,male,25.74,0,no,southeast,12142.5786 339 | 62,male,27.55,1,no,northwest,13937.6665 340 | 50,male,32.3,1,yes,northeast,41919.097 341 | 46,female,27.72,1,no,southeast,8232.6388 342 | 24,female,27.6,0,no,southwest,18955.22017 343 | 62,male,30.02,0,no,northwest,13352.0998 344 | 60,female,27.55,0,no,northeast,13217.0945 345 | 63,male,36.765,0,no,northeast,13981.85035 346 | 49,female,41.47,4,no,southeast,10977.2063 347 | 34,female,29.26,3,no,southeast,6184.2994 348 | 33,male,35.75,2,no,southeast,4889.9995 349 | 46,male,33.345,1,no,northeast,8334.45755 350 | 36,female,29.92,1,no,southeast,5478.0368 351 | 19,male,27.835,0,no,northwest,1635.73365 352 | 57,female,23.18,0,no,northwest,11830.6072 353 | 50,female,25.6,0,no,southwest,8932.084 354 | 30,female,27.7,0,no,southwest,3554.203 355 | 33,male,35.245,0,no,northeast,12404.8791 356 | 18,female,38.28,0,no,southeast,14133.03775 357 | 46,male,27.6,0,no,southwest,24603.04837 358 | 46,male,43.89,3,no,southeast,8944.1151 359 | 47,male,29.83,3,no,northwest,9620.3307 360 | 23,male,41.91,0,no,southeast,1837.2819 361 | 18,female,20.79,0,no,southeast,1607.5101 362 | 48,female,32.3,2,no,northeast,10043.249 363 | 35,male,30.5,1,no,southwest,4751.07 364 | 19,female,21.7,0,yes,southwest,13844.506 365 | 21,female,26.4,1,no,southwest,2597.779 366 | 21,female,21.89,2,no,southeast,3180.5101 367 | 49,female,30.78,1,no,northeast,9778.3472 368 | 56,female,32.3,3,no,northeast,13430.265 369 | 42,female,24.985,2,no,northwest,8017.06115 370 | 44,male,32.015,2,no,northwest,8116.26885 371 | 18,male,30.4,3,no,northeast,3481.868 372 | 61,female,21.09,0,no,northwest,13415.0381 373 | 57,female,22.23,0,no,northeast,12029.2867 374 | 42,female,33.155,1,no,northeast,7639.41745 375 | 26,male,32.9,2,yes,southwest,36085.219 376 | 20,male,33.33,0,no,southeast,1391.5287 377 | 23,female,28.31,0,yes,northwest,18033.9679 378 | 39,female,24.89,3,yes,northeast,21659.9301 379 | 24,male,40.15,0,yes,southeast,38126.2465 380 | 64,female,30.115,3,no,northwest,16455.70785 381 | 62,male,31.46,1,no,southeast,27000.98473 382 | 27,female,17.955,2,yes,northeast,15006.57945 383 | 55,male,30.685,0,yes,northeast,42303.69215 384 | 55,male,33,0,no,southeast,20781.48892 385 | 35,female,43.34,2,no,southeast,5846.9176 386 | 44,male,22.135,2,no,northeast,8302.53565 387 | 19,male,34.4,0,no,southwest,1261.859 388 | 58,female,39.05,0,no,southeast,11856.4115 389 | 50,male,25.365,2,no,northwest,30284.64294 390 | 26,female,22.61,0,no,northwest,3176.8159 391 | 24,female,30.21,3,no,northwest,4618.0799 392 | 48,male,35.625,4,no,northeast,10736.87075 393 | 19,female,37.43,0,no,northwest,2138.0707 394 | 48,male,31.445,1,no,northeast,8964.06055 395 | 49,male,31.35,1,no,northeast,9290.1395 396 | 46,female,32.3,2,no,northeast,9411.005 397 | 46,male,19.855,0,no,northwest,7526.70645 398 | 43,female,34.4,3,no,southwest,8522.003 399 | 21,male,31.02,0,no,southeast,16586.49771 400 | 64,male,25.6,2,no,southwest,14988.432 401 | 18,female,38.17,0,no,southeast,1631.6683 402 | 51,female,20.6,0,no,southwest,9264.797 403 | 47,male,47.52,1,no,southeast,8083.9198 404 | 64,female,32.965,0,no,northwest,14692.66935 405 | 49,male,32.3,3,no,northwest,10269.46 406 | 31,male,20.4,0,no,southwest,3260.199 407 | 52,female,38.38,2,no,northeast,11396.9002 408 | 33,female,24.31,0,no,southeast,4185.0979 409 | 47,female,23.6,1,no,southwest,8539.671 410 | 38,male,21.12,3,no,southeast,6652.5288 411 | 32,male,30.03,1,no,southeast,4074.4537 412 | 19,male,17.48,0,no,northwest,1621.3402 413 | 44,female,20.235,1,yes,northeast,19594.80965 414 | 26,female,17.195,2,yes,northeast,14455.64405 415 | 25,male,23.9,5,no,southwest,5080.096 416 | 19,female,35.15,0,no,northwest,2134.9015 417 | 43,female,35.64,1,no,southeast,7345.7266 418 | 52,male,34.1,0,no,southeast,9140.951 419 | 36,female,22.6,2,yes,southwest,18608.262 420 | 64,male,39.16,1,no,southeast,14418.2804 421 | 63,female,26.98,0,yes,northwest,28950.4692 422 | 64,male,33.88,0,yes,southeast,46889.2612 423 | 61,male,35.86,0,yes,southeast,46599.1084 424 | 40,male,32.775,1,yes,northeast,39125.33225 425 | 25,male,30.59,0,no,northeast,2727.3951 426 | 48,male,30.2,2,no,southwest,8968.33 427 | 45,male,24.31,5,no,southeast,9788.8659 428 | 38,female,27.265,1,no,northeast,6555.07035 429 | 18,female,29.165,0,no,northeast,7323.734819 430 | 21,female,16.815,1,no,northeast,3167.45585 431 | 27,female,30.4,3,no,northwest,18804.7524 432 | 19,male,33.1,0,no,southwest,23082.95533 433 | 29,female,20.235,2,no,northwest,4906.40965 434 | 42,male,26.9,0,no,southwest,5969.723 435 | 60,female,30.5,0,no,southwest,12638.195 436 | 31,male,28.595,1,no,northwest,4243.59005 437 | 60,male,33.11,3,no,southeast,13919.8229 438 | 22,male,31.73,0,no,northeast,2254.7967 439 | 35,male,28.9,3,no,southwest,5926.846 440 | 52,female,46.75,5,no,southeast,12592.5345 441 | 26,male,29.45,0,no,northeast,2897.3235 442 | 31,female,32.68,1,no,northwest,4738.2682 443 | 33,female,33.5,0,yes,southwest,37079.372 444 | 18,male,43.01,0,no,southeast,1149.3959 445 | 59,female,36.52,1,no,southeast,28287.89766 446 | 56,male,26.695,1,yes,northwest,26109.32905 447 | 45,female,33.1,0,no,southwest,7345.084 448 | 60,male,29.64,0,no,northeast,12730.9996 449 | 56,female,25.65,0,no,northwest,11454.0215 450 | 40,female,29.6,0,no,southwest,5910.944 451 | 35,male,38.6,1,no,southwest,4762.329 452 | 39,male,29.6,4,no,southwest,7512.267 453 | 30,male,24.13,1,no,northwest,4032.2407 454 | 24,male,23.4,0,no,southwest,1969.614 455 | 20,male,29.735,0,no,northwest,1769.53165 456 | 32,male,46.53,2,no,southeast,4686.3887 457 | 59,male,37.4,0,no,southwest,21797.0004 458 | 55,female,30.14,2,no,southeast,11881.9696 459 | 57,female,30.495,0,no,northwest,11840.77505 460 | 56,male,39.6,0,no,southwest,10601.412 461 | 40,female,33,3,no,southeast,7682.67 462 | 49,female,36.63,3,no,southeast,10381.4787 463 | 42,male,30,0,yes,southwest,22144.032 464 | 62,female,38.095,2,no,northeast,15230.32405 465 | 56,male,25.935,0,no,northeast,11165.41765 466 | 19,male,25.175,0,no,northwest,1632.03625 467 | 30,female,28.38,1,yes,southeast,19521.9682 468 | 60,female,28.7,1,no,southwest,13224.693 469 | 56,female,33.82,2,no,northwest,12643.3778 470 | 28,female,24.32,1,no,northeast,23288.9284 471 | 18,female,24.09,1,no,southeast,2201.0971 472 | 27,male,32.67,0,no,southeast,2497.0383 473 | 18,female,30.115,0,no,northeast,2203.47185 474 | 19,female,29.8,0,no,southwest,1744.465 475 | 47,female,33.345,0,no,northeast,20878.78443 476 | 54,male,25.1,3,yes,southwest,25382.297 477 | 61,male,28.31,1,yes,northwest,28868.6639 478 | 24,male,28.5,0,yes,northeast,35147.52848 479 | 25,male,35.625,0,no,northwest,2534.39375 480 | 21,male,36.85,0,no,southeast,1534.3045 481 | 23,male,32.56,0,no,southeast,1824.2854 482 | 63,male,41.325,3,no,northwest,15555.18875 483 | 49,male,37.51,2,no,southeast,9304.7019 484 | 18,female,31.35,0,no,southeast,1622.1885 485 | 51,female,39.5,1,no,southwest,9880.068 486 | 48,male,34.3,3,no,southwest,9563.029 487 | 31,female,31.065,0,no,northeast,4347.02335 488 | 54,female,21.47,3,no,northwest,12475.3513 489 | 19,male,28.7,0,no,southwest,1253.936 490 | 44,female,38.06,0,yes,southeast,48885.13561 491 | 53,male,31.16,1,no,northwest,10461.9794 492 | 19,female,32.9,0,no,southwest,1748.774 493 | 61,female,25.08,0,no,southeast,24513.09126 494 | 18,female,25.08,0,no,northeast,2196.4732 495 | 61,male,43.4,0,no,southwest,12574.049 496 | 21,male,25.7,4,yes,southwest,17942.106 497 | 20,male,27.93,0,no,northeast,1967.0227 498 | 31,female,23.6,2,no,southwest,4931.647 499 | 45,male,28.7,2,no,southwest,8027.968 500 | 44,female,23.98,2,no,southeast,8211.1002 501 | 62,female,39.2,0,no,southwest,13470.86 502 | 29,male,34.4,0,yes,southwest,36197.699 503 | 43,male,26.03,0,no,northeast,6837.3687 504 | 51,male,23.21,1,yes,southeast,22218.1149 505 | 19,male,30.25,0,yes,southeast,32548.3405 506 | 38,female,28.93,1,no,southeast,5974.3847 507 | 37,male,30.875,3,no,northwest,6796.86325 508 | 22,male,31.35,1,no,northwest,2643.2685 509 | 21,male,23.75,2,no,northwest,3077.0955 510 | 24,female,25.27,0,no,northeast,3044.2133 511 | 57,female,28.7,0,no,southwest,11455.28 512 | 56,male,32.11,1,no,northeast,11763.0009 513 | 27,male,33.66,0,no,southeast,2498.4144 514 | 51,male,22.42,0,no,northeast,9361.3268 515 | 19,male,30.4,0,no,southwest,1256.299 516 | 39,male,28.3,1,yes,southwest,21082.16 517 | 58,male,35.7,0,no,southwest,11362.755 518 | 20,male,35.31,1,no,southeast,27724.28875 519 | 45,male,30.495,2,no,northwest,8413.46305 520 | 35,female,31,1,no,southwest,5240.765 521 | 31,male,30.875,0,no,northeast,3857.75925 522 | 50,female,27.36,0,no,northeast,25656.57526 523 | 32,female,44.22,0,no,southeast,3994.1778 524 | 51,female,33.915,0,no,northeast,9866.30485 525 | 38,female,37.73,0,no,southeast,5397.6167 526 | 42,male,26.07,1,yes,southeast,38245.59327 527 | 18,female,33.88,0,no,southeast,11482.63485 528 | 19,female,30.59,2,no,northwest,24059.68019 529 | 51,female,25.8,1,no,southwest,9861.025 530 | 46,male,39.425,1,no,northeast,8342.90875 531 | 18,male,25.46,0,no,northeast,1708.0014 532 | 57,male,42.13,1,yes,southeast,48675.5177 533 | 62,female,31.73,0,no,northeast,14043.4767 534 | 59,male,29.7,2,no,southeast,12925.886 535 | 37,male,36.19,0,no,southeast,19214.70553 536 | 64,male,40.48,0,no,southeast,13831.1152 537 | 38,male,28.025,1,no,northeast,6067.12675 538 | 33,female,38.9,3,no,southwest,5972.378 539 | 46,female,30.2,2,no,southwest,8825.086 540 | 46,female,28.05,1,no,southeast,8233.0975 541 | 53,male,31.35,0,no,southeast,27346.04207 542 | 34,female,38,3,no,southwest,6196.448 543 | 20,female,31.79,2,no,southeast,3056.3881 544 | 63,female,36.3,0,no,southeast,13887.204 545 | 54,female,47.41,0,yes,southeast,63770.42801 546 | 54,male,30.21,0,no,northwest,10231.4999 547 | 49,male,25.84,2,yes,northwest,23807.2406 548 | 28,male,35.435,0,no,northeast,3268.84665 549 | 54,female,46.7,2,no,southwest,11538.421 550 | 25,female,28.595,0,no,northeast,3213.62205 551 | 43,female,46.2,0,yes,southeast,45863.205 552 | 63,male,30.8,0,no,southwest,13390.559 553 | 32,female,28.93,0,no,southeast,3972.9247 554 | 62,male,21.4,0,no,southwest,12957.118 555 | 52,female,31.73,2,no,northwest,11187.6567 556 | 25,female,41.325,0,no,northeast,17878.90068 557 | 28,male,23.8,2,no,southwest,3847.674 558 | 46,male,33.44,1,no,northeast,8334.5896 559 | 34,male,34.21,0,no,southeast,3935.1799 560 | 35,female,34.105,3,yes,northwest,39983.42595 561 | 19,male,35.53,0,no,northwest,1646.4297 562 | 46,female,19.95,2,no,northwest,9193.8385 563 | 54,female,32.68,0,no,northeast,10923.9332 564 | 27,male,30.5,0,no,southwest,2494.022 565 | 50,male,44.77,1,no,southeast,9058.7303 566 | 18,female,32.12,2,no,southeast,2801.2588 567 | 19,female,30.495,0,no,northwest,2128.43105 568 | 38,female,40.565,1,no,northwest,6373.55735 569 | 41,male,30.59,2,no,northwest,7256.7231 570 | 49,female,31.9,5,no,southwest,11552.904 571 | 48,male,40.565,2,yes,northwest,45702.02235 572 | 31,female,29.1,0,no,southwest,3761.292 573 | 18,female,37.29,1,no,southeast,2219.4451 574 | 30,female,43.12,2,no,southeast,4753.6368 575 | 62,female,36.86,1,no,northeast,31620.00106 576 | 57,female,34.295,2,no,northeast,13224.05705 577 | 58,female,27.17,0,no,northwest,12222.8983 578 | 22,male,26.84,0,no,southeast,1664.9996 579 | 31,female,38.095,1,yes,northeast,58571.07448 580 | 52,male,30.2,1,no,southwest,9724.53 581 | 25,female,23.465,0,no,northeast,3206.49135 582 | 59,male,25.46,1,no,northeast,12913.9924 583 | 19,male,30.59,0,no,northwest,1639.5631 584 | 39,male,45.43,2,no,southeast,6356.2707 585 | 32,female,23.65,1,no,southeast,17626.23951 586 | 19,male,20.7,0,no,southwest,1242.816 587 | 33,female,28.27,1,no,southeast,4779.6023 588 | 21,male,20.235,3,no,northeast,3861.20965 589 | 34,female,30.21,1,yes,northwest,43943.8761 590 | 61,female,35.91,0,no,northeast,13635.6379 591 | 38,female,30.69,1,no,southeast,5976.8311 592 | 58,female,29,0,no,southwest,11842.442 593 | 47,male,19.57,1,no,northwest,8428.0693 594 | 20,male,31.13,2,no,southeast,2566.4707 595 | 21,female,21.85,1,yes,northeast,15359.1045 596 | 41,male,40.26,0,no,southeast,5709.1644 597 | 46,female,33.725,1,no,northeast,8823.98575 598 | 42,female,29.48,2,no,southeast,7640.3092 599 | 34,female,33.25,1,no,northeast,5594.8455 600 | 43,male,32.6,2,no,southwest,7441.501 601 | 52,female,37.525,2,no,northwest,33471.97189 602 | 18,female,39.16,0,no,southeast,1633.0444 603 | 51,male,31.635,0,no,northwest,9174.13565 604 | 56,female,25.3,0,no,southwest,11070.535 605 | 64,female,39.05,3,no,southeast,16085.1275 606 | 19,female,28.31,0,yes,northwest,17468.9839 607 | 51,female,34.1,0,no,southeast,9283.562 608 | 27,female,25.175,0,no,northeast,3558.62025 609 | 59,female,23.655,0,yes,northwest,25678.77845 610 | 28,male,26.98,2,no,northeast,4435.0942 611 | 30,male,37.8,2,yes,southwest,39241.442 612 | 47,female,29.37,1,no,southeast,8547.6913 613 | 38,female,34.8,2,no,southwest,6571.544 614 | 18,female,33.155,0,no,northeast,2207.69745 615 | 34,female,19,3,no,northeast,6753.038 616 | 20,female,33,0,no,southeast,1880.07 617 | 47,female,36.63,1,yes,southeast,42969.8527 618 | 56,female,28.595,0,no,northeast,11658.11505 619 | 49,male,25.6,2,yes,southwest,23306.547 620 | 19,female,33.11,0,yes,southeast,34439.8559 621 | 55,female,37.1,0,no,southwest,10713.644 622 | 30,male,31.4,1,no,southwest,3659.346 623 | 37,male,34.1,4,yes,southwest,40182.246 624 | 49,female,21.3,1,no,southwest,9182.17 625 | 18,male,33.535,0,yes,northeast,34617.84065 626 | 59,male,28.785,0,no,northwest,12129.61415 627 | 29,female,26.03,0,no,northwest,3736.4647 628 | 36,male,28.88,3,no,northeast,6748.5912 629 | 33,male,42.46,1,no,southeast,11326.71487 630 | 58,male,38,0,no,southwest,11365.952 631 | 44,female,38.95,0,yes,northwest,42983.4585 632 | 53,male,36.1,1,no,southwest,10085.846 633 | 24,male,29.3,0,no,southwest,1977.815 634 | 29,female,35.53,0,no,southeast,3366.6697 635 | 40,male,22.705,2,no,northeast,7173.35995 636 | 51,male,39.7,1,no,southwest,9391.346 637 | 64,male,38.19,0,no,northeast,14410.9321 638 | 19,female,24.51,1,no,northwest,2709.1119 639 | 35,female,38.095,2,no,northeast,24915.04626 640 | 39,male,26.41,0,yes,northeast,20149.3229 641 | 56,male,33.66,4,no,southeast,12949.1554 642 | 33,male,42.4,5,no,southwest,6666.243 643 | 42,male,28.31,3,yes,northwest,32787.45859 644 | 61,male,33.915,0,no,northeast,13143.86485 645 | 23,female,34.96,3,no,northwest,4466.6214 646 | 43,male,35.31,2,no,southeast,18806.14547 647 | 48,male,30.78,3,no,northeast,10141.1362 648 | 39,male,26.22,1,no,northwest,6123.5688 649 | 40,female,23.37,3,no,northeast,8252.2843 650 | 18,male,28.5,0,no,northeast,1712.227 651 | 58,female,32.965,0,no,northeast,12430.95335 652 | 49,female,42.68,2,no,southeast,9800.8882 653 | 53,female,39.6,1,no,southeast,10579.711 654 | 48,female,31.13,0,no,southeast,8280.6227 655 | 45,female,36.3,2,no,southeast,8527.532 656 | 59,female,35.2,0,no,southeast,12244.531 657 | 52,female,25.3,2,yes,southeast,24667.419 658 | 26,female,42.4,1,no,southwest,3410.324 659 | 27,male,33.155,2,no,northwest,4058.71245 660 | 48,female,35.91,1,no,northeast,26392.26029 661 | 57,female,28.785,4,no,northeast,14394.39815 662 | 37,male,46.53,3,no,southeast,6435.6237 663 | 57,female,23.98,1,no,southeast,22192.43711 664 | 32,female,31.54,1,no,northeast,5148.5526 665 | 18,male,33.66,0,no,southeast,1136.3994 666 | 64,female,22.99,0,yes,southeast,27037.9141 667 | 43,male,38.06,2,yes,southeast,42560.4304 668 | 49,male,28.7,1,no,southwest,8703.456 669 | 40,female,32.775,2,yes,northwest,40003.33225 670 | 62,male,32.015,0,yes,northeast,45710.20785 671 | 40,female,29.81,1,no,southeast,6500.2359 672 | 30,male,31.57,3,no,southeast,4837.5823 673 | 29,female,31.16,0,no,northeast,3943.5954 674 | 36,male,29.7,0,no,southeast,4399.731 675 | 41,female,31.02,0,no,southeast,6185.3208 676 | 44,female,43.89,2,yes,southeast,46200.9851 677 | 45,male,21.375,0,no,northwest,7222.78625 678 | 55,female,40.81,3,no,southeast,12485.8009 679 | 60,male,31.35,3,yes,northwest,46130.5265 680 | 56,male,36.1,3,no,southwest,12363.547 681 | 49,female,23.18,2,no,northwest,10156.7832 682 | 21,female,17.4,1,no,southwest,2585.269 683 | 19,male,20.3,0,no,southwest,1242.26 684 | 39,male,35.3,2,yes,southwest,40103.89 685 | 53,male,24.32,0,no,northwest,9863.4718 686 | 33,female,18.5,1,no,southwest,4766.022 687 | 53,male,26.41,2,no,northeast,11244.3769 688 | 42,male,26.125,2,no,northeast,7729.64575 689 | 40,male,41.69,0,no,southeast,5438.7491 690 | 47,female,24.1,1,no,southwest,26236.57997 691 | 27,male,31.13,1,yes,southeast,34806.4677 692 | 21,male,27.36,0,no,northeast,2104.1134 693 | 47,male,36.2,1,no,southwest,8068.185 694 | 20,male,32.395,1,no,northwest,2362.22905 695 | 24,male,23.655,0,no,northwest,2352.96845 696 | 27,female,34.8,1,no,southwest,3577.999 697 | 26,female,40.185,0,no,northwest,3201.24515 698 | 53,female,32.3,2,no,northeast,29186.48236 699 | 41,male,35.75,1,yes,southeast,40273.6455 700 | 56,male,33.725,0,no,northwest,10976.24575 701 | 23,female,39.27,2,no,southeast,3500.6123 702 | 21,female,34.87,0,no,southeast,2020.5523 703 | 50,female,44.745,0,no,northeast,9541.69555 704 | 53,male,41.47,0,no,southeast,9504.3103 705 | 34,female,26.41,1,no,northwest,5385.3379 706 | 47,female,29.545,1,no,northwest,8930.93455 707 | 33,female,32.9,2,no,southwest,5375.038 708 | 51,female,38.06,0,yes,southeast,44400.4064 709 | 49,male,28.69,3,no,northwest,10264.4421 710 | 31,female,30.495,3,no,northeast,6113.23105 711 | 36,female,27.74,0,no,northeast,5469.0066 712 | 18,male,35.2,1,no,southeast,1727.54 713 | 50,female,23.54,2,no,southeast,10107.2206 714 | 43,female,30.685,2,no,northwest,8310.83915 715 | 20,male,40.47,0,no,northeast,1984.4533 716 | 24,female,22.6,0,no,southwest,2457.502 717 | 60,male,28.9,0,no,southwest,12146.971 718 | 49,female,22.61,1,no,northwest,9566.9909 719 | 60,male,24.32,1,no,northwest,13112.6048 720 | 51,female,36.67,2,no,northwest,10848.1343 721 | 58,female,33.44,0,no,northwest,12231.6136 722 | 51,female,40.66,0,no,northeast,9875.6804 723 | 53,male,36.6,3,no,southwest,11264.541 724 | 62,male,37.4,0,no,southwest,12979.358 725 | 19,male,35.4,0,no,southwest,1263.249 726 | 50,female,27.075,1,no,northeast,10106.13425 727 | 30,female,39.05,3,yes,southeast,40932.4295 728 | 41,male,28.405,1,no,northwest,6664.68595 729 | 29,female,21.755,1,yes,northeast,16657.71745 730 | 18,female,40.28,0,no,northeast,2217.6012 731 | 41,female,36.08,1,no,southeast,6781.3542 732 | 35,male,24.42,3,yes,southeast,19361.9988 733 | 53,male,21.4,1,no,southwest,10065.413 734 | 24,female,30.1,3,no,southwest,4234.927 735 | 48,female,27.265,1,no,northeast,9447.25035 736 | 59,female,32.1,3,no,southwest,14007.222 737 | 49,female,34.77,1,no,northwest,9583.8933 738 | 37,female,38.39,0,yes,southeast,40419.0191 739 | 26,male,23.7,2,no,southwest,3484.331 740 | 23,male,31.73,3,yes,northeast,36189.1017 741 | 29,male,35.5,2,yes,southwest,44585.45587 742 | 45,male,24.035,2,no,northeast,8604.48365 743 | 27,male,29.15,0,yes,southeast,18246.4955 744 | 53,male,34.105,0,yes,northeast,43254.41795 745 | 31,female,26.62,0,no,southeast,3757.8448 746 | 50,male,26.41,0,no,northwest,8827.2099 747 | 50,female,30.115,1,no,northwest,9910.35985 748 | 34,male,27,2,no,southwest,11737.84884 749 | 19,male,21.755,0,no,northwest,1627.28245 750 | 47,female,36,1,no,southwest,8556.907 751 | 28,male,30.875,0,no,northwest,3062.50825 752 | 37,female,26.4,0,yes,southeast,19539.243 753 | 21,male,28.975,0,no,northwest,1906.35825 754 | 64,male,37.905,0,no,northwest,14210.53595 755 | 58,female,22.77,0,no,southeast,11833.7823 756 | 24,male,33.63,4,no,northeast,17128.42608 757 | 31,male,27.645,2,no,northeast,5031.26955 758 | 39,female,22.8,3,no,northeast,7985.815 759 | 47,female,27.83,0,yes,southeast,23065.4207 760 | 30,male,37.43,3,no,northeast,5428.7277 761 | 18,male,38.17,0,yes,southeast,36307.7983 762 | 22,female,34.58,2,no,northeast,3925.7582 763 | 23,male,35.2,1,no,southwest,2416.955 764 | 33,male,27.1,1,yes,southwest,19040.876 765 | 27,male,26.03,0,no,northeast,3070.8087 766 | 45,female,25.175,2,no,northeast,9095.06825 767 | 57,female,31.825,0,no,northwest,11842.62375 768 | 47,male,32.3,1,no,southwest,8062.764 769 | 42,female,29,1,no,southwest,7050.642 770 | 64,female,39.7,0,no,southwest,14319.031 771 | 38,female,19.475,2,no,northwest,6933.24225 772 | 61,male,36.1,3,no,southwest,27941.28758 773 | 53,female,26.7,2,no,southwest,11150.78 774 | 44,female,36.48,0,no,northeast,12797.20962 775 | 19,female,28.88,0,yes,northwest,17748.5062 776 | 41,male,34.2,2,no,northwest,7261.741 777 | 51,male,33.33,3,no,southeast,10560.4917 778 | 40,male,32.3,2,no,northwest,6986.697 779 | 45,male,39.805,0,no,northeast,7448.40395 780 | 35,male,34.32,3,no,southeast,5934.3798 781 | 53,male,28.88,0,no,northwest,9869.8102 782 | 30,male,24.4,3,yes,southwest,18259.216 783 | 18,male,41.14,0,no,southeast,1146.7966 784 | 51,male,35.97,1,no,southeast,9386.1613 785 | 50,female,27.6,1,yes,southwest,24520.264 786 | 31,female,29.26,1,no,southeast,4350.5144 787 | 35,female,27.7,3,no,southwest,6414.178 788 | 60,male,36.955,0,no,northeast,12741.16745 789 | 21,male,36.86,0,no,northwest,1917.3184 790 | 29,male,22.515,3,no,northeast,5209.57885 791 | 62,female,29.92,0,no,southeast,13457.9608 792 | 39,female,41.8,0,no,southeast,5662.225 793 | 19,male,27.6,0,no,southwest,1252.407 794 | 22,female,23.18,0,no,northeast,2731.9122 795 | 53,male,20.9,0,yes,southeast,21195.818 796 | 39,female,31.92,2,no,northwest,7209.4918 797 | 27,male,28.5,0,yes,northwest,18310.742 798 | 30,male,44.22,2,no,southeast,4266.1658 799 | 30,female,22.895,1,no,northeast,4719.52405 800 | 58,female,33.1,0,no,southwest,11848.141 801 | 33,male,24.795,0,yes,northeast,17904.52705 802 | 42,female,26.18,1,no,southeast,7046.7222 803 | 64,female,35.97,0,no,southeast,14313.8463 804 | 21,male,22.3,1,no,southwest,2103.08 805 | 18,female,42.24,0,yes,southeast,38792.6856 806 | 23,male,26.51,0,no,southeast,1815.8759 807 | 45,female,35.815,0,no,northwest,7731.85785 808 | 40,female,41.42,1,no,northwest,28476.73499 809 | 19,female,36.575,0,no,northwest,2136.88225 810 | 18,male,30.14,0,no,southeast,1131.5066 811 | 25,male,25.84,1,no,northeast,3309.7926 812 | 46,female,30.8,3,no,southwest,9414.92 813 | 33,female,42.94,3,no,northwest,6360.9936 814 | 54,male,21.01,2,no,southeast,11013.7119 815 | 28,male,22.515,2,no,northeast,4428.88785 816 | 36,male,34.43,2,no,southeast,5584.3057 817 | 20,female,31.46,0,no,southeast,1877.9294 818 | 24,female,24.225,0,no,northwest,2842.76075 819 | 23,male,37.1,3,no,southwest,3597.596 820 | 47,female,26.125,1,yes,northeast,23401.30575 821 | 33,female,35.53,0,yes,northwest,55135.40209 822 | 45,male,33.7,1,no,southwest,7445.918 823 | 26,male,17.67,0,no,northwest,2680.9493 824 | 18,female,31.13,0,no,southeast,1621.8827 825 | 44,female,29.81,2,no,southeast,8219.2039 826 | 60,male,24.32,0,no,northwest,12523.6048 827 | 64,female,31.825,2,no,northeast,16069.08475 828 | 56,male,31.79,2,yes,southeast,43813.8661 829 | 36,male,28.025,1,yes,northeast,20773.62775 830 | 41,male,30.78,3,yes,northeast,39597.4072 831 | 39,male,21.85,1,no,northwest,6117.4945 832 | 63,male,33.1,0,no,southwest,13393.756 833 | 36,female,25.84,0,no,northwest,5266.3656 834 | 28,female,23.845,2,no,northwest,4719.73655 835 | 58,male,34.39,0,no,northwest,11743.9341 836 | 36,male,33.82,1,no,northwest,5377.4578 837 | 42,male,35.97,2,no,southeast,7160.3303 838 | 36,male,31.5,0,no,southwest,4402.233 839 | 56,female,28.31,0,no,northeast,11657.7189 840 | 35,female,23.465,2,no,northeast,6402.29135 841 | 59,female,31.35,0,no,northwest,12622.1795 842 | 21,male,31.1,0,no,southwest,1526.312 843 | 59,male,24.7,0,no,northeast,12323.936 844 | 23,female,32.78,2,yes,southeast,36021.0112 845 | 57,female,29.81,0,yes,southeast,27533.9129 846 | 53,male,30.495,0,no,northeast,10072.05505 847 | 60,female,32.45,0,yes,southeast,45008.9555 848 | 51,female,34.2,1,no,southwest,9872.701 849 | 23,male,50.38,1,no,southeast,2438.0552 850 | 27,female,24.1,0,no,southwest,2974.126 851 | 55,male,32.775,0,no,northwest,10601.63225 852 | 37,female,30.78,0,yes,northeast,37270.1512 853 | 61,male,32.3,2,no,northwest,14119.62 854 | 46,female,35.53,0,yes,northeast,42111.6647 855 | 53,female,23.75,2,no,northeast,11729.6795 856 | 49,female,23.845,3,yes,northeast,24106.91255 857 | 20,female,29.6,0,no,southwest,1875.344 858 | 48,female,33.11,0,yes,southeast,40974.1649 859 | 25,male,24.13,0,yes,northwest,15817.9857 860 | 25,female,32.23,1,no,southeast,18218.16139 861 | 57,male,28.1,0,no,southwest,10965.446 862 | 37,female,47.6,2,yes,southwest,46113.511 863 | 38,female,28,3,no,southwest,7151.092 864 | 55,female,33.535,2,no,northwest,12269.68865 865 | 36,female,19.855,0,no,northeast,5458.04645 866 | 51,male,25.4,0,no,southwest,8782.469 867 | 40,male,29.9,2,no,southwest,6600.361 868 | 18,male,37.29,0,no,southeast,1141.4451 869 | 57,male,43.7,1,no,southwest,11576.13 870 | 61,male,23.655,0,no,northeast,13129.60345 871 | 25,female,24.3,3,no,southwest,4391.652 872 | 50,male,36.2,0,no,southwest,8457.818 873 | 26,female,29.48,1,no,southeast,3392.3652 874 | 42,male,24.86,0,no,southeast,5966.8874 875 | 43,male,30.1,1,no,southwest,6849.026 876 | 44,male,21.85,3,no,northeast,8891.1395 877 | 23,female,28.12,0,no,northwest,2690.1138 878 | 49,female,27.1,1,no,southwest,26140.3603 879 | 33,male,33.44,5,no,southeast,6653.7886 880 | 41,male,28.8,1,no,southwest,6282.235 881 | 37,female,29.5,2,no,southwest,6311.952 882 | 22,male,34.8,3,no,southwest,3443.064 883 | 23,male,27.36,1,no,northwest,2789.0574 884 | 21,female,22.135,0,no,northeast,2585.85065 885 | 51,female,37.05,3,yes,northeast,46255.1125 886 | 25,male,26.695,4,no,northwest,4877.98105 887 | 32,male,28.93,1,yes,southeast,19719.6947 888 | 57,male,28.975,0,yes,northeast,27218.43725 889 | 36,female,30.02,0,no,northwest,5272.1758 890 | 22,male,39.5,0,no,southwest,1682.597 891 | 57,male,33.63,1,no,northwest,11945.1327 892 | 64,female,26.885,0,yes,northwest,29330.98315 893 | 36,female,29.04,4,no,southeast,7243.8136 894 | 54,male,24.035,0,no,northeast,10422.91665 895 | 47,male,38.94,2,yes,southeast,44202.6536 896 | 62,male,32.11,0,no,northeast,13555.0049 897 | 61,female,44,0,no,southwest,13063.883 898 | 43,female,20.045,2,yes,northeast,19798.05455 899 | 19,male,25.555,1,no,northwest,2221.56445 900 | 18,female,40.26,0,no,southeast,1634.5734 901 | 19,female,22.515,0,no,northwest,2117.33885 902 | 49,male,22.515,0,no,northeast,8688.85885 903 | 60,male,40.92,0,yes,southeast,48673.5588 904 | 26,male,27.265,3,no,northeast,4661.28635 905 | 49,male,36.85,0,no,southeast,8125.7845 906 | 60,female,35.1,0,no,southwest,12644.589 907 | 26,female,29.355,2,no,northeast,4564.19145 908 | 27,male,32.585,3,no,northeast,4846.92015 909 | 44,female,32.34,1,no,southeast,7633.7206 910 | 63,male,39.8,3,no,southwest,15170.069 911 | 32,female,24.6,0,yes,southwest,17496.306 912 | 22,male,28.31,1,no,northwest,2639.0429 913 | 18,male,31.73,0,yes,northeast,33732.6867 914 | 59,female,26.695,3,no,northwest,14382.70905 915 | 44,female,27.5,1,no,southwest,7626.993 916 | 33,male,24.605,2,no,northwest,5257.50795 917 | 24,female,33.99,0,no,southeast,2473.3341 918 | 43,female,26.885,0,yes,northwest,21774.32215 919 | 45,male,22.895,0,yes,northeast,35069.37452 920 | 61,female,28.2,0,no,southwest,13041.921 921 | 35,female,34.21,1,no,southeast,5245.2269 922 | 62,female,25,0,no,southwest,13451.122 923 | 62,female,33.2,0,no,southwest,13462.52 924 | 38,male,31,1,no,southwest,5488.262 925 | 34,male,35.815,0,no,northwest,4320.41085 926 | 43,male,23.2,0,no,southwest,6250.435 927 | 50,male,32.11,2,no,northeast,25333.33284 928 | 19,female,23.4,2,no,southwest,2913.569 929 | 57,female,20.1,1,no,southwest,12032.326 930 | 62,female,39.16,0,no,southeast,13470.8044 931 | 41,male,34.21,1,no,southeast,6289.7549 932 | 26,male,46.53,1,no,southeast,2927.0647 933 | 39,female,32.5,1,no,southwest,6238.298 934 | 46,male,25.8,5,no,southwest,10096.97 935 | 45,female,35.3,0,no,southwest,7348.142 936 | 32,male,37.18,2,no,southeast,4673.3922 937 | 59,female,27.5,0,no,southwest,12233.828 938 | 44,male,29.735,2,no,northeast,32108.66282 939 | 39,female,24.225,5,no,northwest,8965.79575 940 | 18,male,26.18,2,no,southeast,2304.0022 941 | 53,male,29.48,0,no,southeast,9487.6442 942 | 18,male,23.21,0,no,southeast,1121.8739 943 | 50,female,46.09,1,no,southeast,9549.5651 944 | 18,female,40.185,0,no,northeast,2217.46915 945 | 19,male,22.61,0,no,northwest,1628.4709 946 | 62,male,39.93,0,no,southeast,12982.8747 947 | 56,female,35.8,1,no,southwest,11674.13 948 | 42,male,35.8,2,no,southwest,7160.094 949 | 37,male,34.2,1,yes,northeast,39047.285 950 | 42,male,31.255,0,no,northwest,6358.77645 951 | 25,male,29.7,3,yes,southwest,19933.458 952 | 57,male,18.335,0,no,northeast,11534.87265 953 | 51,male,42.9,2,yes,southeast,47462.894 954 | 30,female,28.405,1,no,northwest,4527.18295 955 | 44,male,30.2,2,yes,southwest,38998.546 956 | 34,male,27.835,1,yes,northwest,20009.63365 957 | 31,male,39.49,1,no,southeast,3875.7341 958 | 54,male,30.8,1,yes,southeast,41999.52 959 | 24,male,26.79,1,no,northwest,12609.88702 960 | 43,male,34.96,1,yes,northeast,41034.2214 961 | 48,male,36.67,1,no,northwest,28468.91901 962 | 19,female,39.615,1,no,northwest,2730.10785 963 | 29,female,25.9,0,no,southwest,3353.284 964 | 63,female,35.2,1,no,southeast,14474.675 965 | 46,male,24.795,3,no,northeast,9500.57305 966 | 52,male,36.765,2,no,northwest,26467.09737 967 | 35,male,27.1,1,no,southwest,4746.344 968 | 51,male,24.795,2,yes,northwest,23967.38305 969 | 44,male,25.365,1,no,northwest,7518.02535 970 | 21,male,25.745,2,no,northeast,3279.86855 971 | 39,female,34.32,5,no,southeast,8596.8278 972 | 50,female,28.16,3,no,southeast,10702.6424 973 | 34,female,23.56,0,no,northeast,4992.3764 974 | 22,female,20.235,0,no,northwest,2527.81865 975 | 19,female,40.5,0,no,southwest,1759.338 976 | 26,male,35.42,0,no,southeast,2322.6218 977 | 29,male,22.895,0,yes,northeast,16138.76205 978 | 48,male,40.15,0,no,southeast,7804.1605 979 | 26,male,29.15,1,no,southeast,2902.9065 980 | 45,female,39.995,3,no,northeast,9704.66805 981 | 36,female,29.92,0,no,southeast,4889.0368 982 | 54,male,25.46,1,no,northeast,25517.11363 983 | 34,male,21.375,0,no,northeast,4500.33925 984 | 31,male,25.9,3,yes,southwest,19199.944 985 | 27,female,30.59,1,no,northeast,16796.41194 986 | 20,male,30.115,5,no,northeast,4915.05985 987 | 44,female,25.8,1,no,southwest,7624.63 988 | 43,male,30.115,3,no,northwest,8410.04685 989 | 45,female,27.645,1,no,northwest,28340.18885 990 | 34,male,34.675,0,no,northeast,4518.82625 991 | 24,female,20.52,0,yes,northeast,14571.8908 992 | 26,female,19.8,1,no,southwest,3378.91 993 | 38,female,27.835,2,no,northeast,7144.86265 994 | 50,female,31.6,2,no,southwest,10118.424 995 | 38,male,28.27,1,no,southeast,5484.4673 996 | 27,female,20.045,3,yes,northwest,16420.49455 997 | 39,female,23.275,3,no,northeast,7986.47525 998 | 39,female,34.1,3,no,southwest,7418.522 999 | 63,female,36.85,0,no,southeast,13887.9685 1000 | 33,female,36.29,3,no,northeast,6551.7501 1001 | 36,female,26.885,0,no,northwest,5267.81815 1002 | 30,male,22.99,2,yes,northwest,17361.7661 1003 | 24,male,32.7,0,yes,southwest,34472.841 1004 | 24,male,25.8,0,no,southwest,1972.95 1005 | 48,male,29.6,0,no,southwest,21232.18226 1006 | 47,male,19.19,1,no,northeast,8627.5411 1007 | 29,male,31.73,2,no,northwest,4433.3877 1008 | 28,male,29.26,2,no,northeast,4438.2634 1009 | 47,male,28.215,3,yes,northwest,24915.22085 1010 | 25,male,24.985,2,no,northeast,23241.47453 1011 | 51,male,27.74,1,no,northeast,9957.7216 1012 | 48,female,22.8,0,no,southwest,8269.044 1013 | 43,male,20.13,2,yes,southeast,18767.7377 1014 | 61,female,33.33,4,no,southeast,36580.28216 1015 | 48,male,32.3,1,no,northwest,8765.249 1016 | 38,female,27.6,0,no,southwest,5383.536 1017 | 59,male,25.46,0,no,northwest,12124.9924 1018 | 19,female,24.605,1,no,northwest,2709.24395 1019 | 26,female,34.2,2,no,southwest,3987.926 1020 | 54,female,35.815,3,no,northwest,12495.29085 1021 | 21,female,32.68,2,no,northwest,26018.95052 1022 | 51,male,37,0,no,southwest,8798.593 1023 | 22,female,31.02,3,yes,southeast,35595.5898 1024 | 47,male,36.08,1,yes,southeast,42211.1382 1025 | 18,male,23.32,1,no,southeast,1711.0268 1026 | 47,female,45.32,1,no,southeast,8569.8618 1027 | 21,female,34.6,0,no,southwest,2020.177 1028 | 19,male,26.03,1,yes,northwest,16450.8947 1029 | 23,male,18.715,0,no,northwest,21595.38229 1030 | 54,male,31.6,0,no,southwest,9850.432 1031 | 37,female,17.29,2,no,northeast,6877.9801 1032 | 46,female,23.655,1,yes,northwest,21677.28345 1033 | 55,female,35.2,0,yes,southeast,44423.803 1034 | 30,female,27.93,0,no,northeast,4137.5227 1035 | 18,male,21.565,0,yes,northeast,13747.87235 1036 | 61,male,38.38,0,no,northwest,12950.0712 1037 | 54,female,23,3,no,southwest,12094.478 1038 | 22,male,37.07,2,yes,southeast,37484.4493 1039 | 45,female,30.495,1,yes,northwest,39725.51805 1040 | 22,male,28.88,0,no,northeast,2250.8352 1041 | 19,male,27.265,2,no,northwest,22493.65964 1042 | 35,female,28.025,0,yes,northwest,20234.85475 1043 | 18,male,23.085,0,no,northeast,1704.70015 1044 | 20,male,30.685,0,yes,northeast,33475.81715 1045 | 28,female,25.8,0,no,southwest,3161.454 1046 | 55,male,35.245,1,no,northeast,11394.06555 1047 | 43,female,24.7,2,yes,northwest,21880.82 1048 | 43,female,25.08,0,no,northeast,7325.0482 1049 | 22,male,52.58,1,yes,southeast,44501.3982 1050 | 25,female,22.515,1,no,northwest,3594.17085 1051 | 49,male,30.9,0,yes,southwest,39727.614 1052 | 44,female,36.955,1,no,northwest,8023.13545 1053 | 64,male,26.41,0,no,northeast,14394.5579 1054 | 49,male,29.83,1,no,northeast,9288.0267 1055 | 47,male,29.8,3,yes,southwest,25309.489 1056 | 27,female,21.47,0,no,northwest,3353.4703 1057 | 55,male,27.645,0,no,northwest,10594.50155 1058 | 48,female,28.9,0,no,southwest,8277.523 1059 | 45,female,31.79,0,no,southeast,17929.30337 1060 | 24,female,39.49,0,no,southeast,2480.9791 1061 | 32,male,33.82,1,no,northwest,4462.7218 1062 | 24,male,32.01,0,no,southeast,1981.5819 1063 | 57,male,27.94,1,no,southeast,11554.2236 1064 | 59,male,41.14,1,yes,southeast,48970.2476 1065 | 36,male,28.595,3,no,northwest,6548.19505 1066 | 29,female,25.6,4,no,southwest,5708.867 1067 | 42,female,25.3,1,no,southwest,7045.499 1068 | 48,male,37.29,2,no,southeast,8978.1851 1069 | 39,male,42.655,0,no,northeast,5757.41345 1070 | 63,male,21.66,1,no,northwest,14349.8544 1071 | 54,female,31.9,1,no,southeast,10928.849 1072 | 37,male,37.07,1,yes,southeast,39871.7043 1073 | 63,male,31.445,0,no,northeast,13974.45555 1074 | 21,male,31.255,0,no,northwest,1909.52745 1075 | 54,female,28.88,2,no,northeast,12096.6512 1076 | 60,female,18.335,0,no,northeast,13204.28565 1077 | 32,female,29.59,1,no,southeast,4562.8421 1078 | 47,female,32,1,no,southwest,8551.347 1079 | 21,male,26.03,0,no,northeast,2102.2647 1080 | 28,male,31.68,0,yes,southeast,34672.1472 1081 | 63,male,33.66,3,no,southeast,15161.5344 1082 | 18,male,21.78,2,no,southeast,11884.04858 1083 | 32,male,27.835,1,no,northwest,4454.40265 1084 | 38,male,19.95,1,no,northwest,5855.9025 1085 | 32,male,31.5,1,no,southwest,4076.497 1086 | 62,female,30.495,2,no,northwest,15019.76005 1087 | 39,female,18.3,5,yes,southwest,19023.26 1088 | 55,male,28.975,0,no,northeast,10796.35025 1089 | 57,male,31.54,0,no,northwest,11353.2276 1090 | 52,male,47.74,1,no,southeast,9748.9106 1091 | 56,male,22.1,0,no,southwest,10577.087 1092 | 47,male,36.19,0,yes,southeast,41676.0811 1093 | 55,female,29.83,0,no,northeast,11286.5387 1094 | 23,male,32.7,3,no,southwest,3591.48 1095 | 22,female,30.4,0,yes,northwest,33907.548 1096 | 50,female,33.7,4,no,southwest,11299.343 1097 | 18,female,31.35,4,no,northeast,4561.1885 1098 | 51,female,34.96,2,yes,northeast,44641.1974 1099 | 22,male,33.77,0,no,southeast,1674.6323 1100 | 52,female,30.875,0,no,northeast,23045.56616 1101 | 25,female,33.99,1,no,southeast,3227.1211 1102 | 33,female,19.095,2,yes,northeast,16776.30405 1103 | 53,male,28.6,3,no,southwest,11253.421 1104 | 29,male,38.94,1,no,southeast,3471.4096 1105 | 58,male,36.08,0,no,southeast,11363.2832 1106 | 37,male,29.8,0,no,southwest,20420.60465 1107 | 54,female,31.24,0,no,southeast,10338.9316 1108 | 49,female,29.925,0,no,northwest,8988.15875 1109 | 50,female,26.22,2,no,northwest,10493.9458 1110 | 26,male,30,1,no,southwest,2904.088 1111 | 45,male,20.35,3,no,southeast,8605.3615 1112 | 54,female,32.3,1,no,northeast,11512.405 1113 | 38,male,38.39,3,yes,southeast,41949.2441 1114 | 48,female,25.85,3,yes,southeast,24180.9335 1115 | 28,female,26.315,3,no,northwest,5312.16985 1116 | 23,male,24.51,0,no,northeast,2396.0959 1117 | 55,male,32.67,1,no,southeast,10807.4863 1118 | 41,male,29.64,5,no,northeast,9222.4026 1119 | 25,male,33.33,2,yes,southeast,36124.5737 1120 | 33,male,35.75,1,yes,southeast,38282.7495 1121 | 30,female,19.95,3,no,northwest,5693.4305 1122 | 23,female,31.4,0,yes,southwest,34166.273 1123 | 46,male,38.17,2,no,southeast,8347.1643 1124 | 53,female,36.86,3,yes,northwest,46661.4424 1125 | 27,female,32.395,1,no,northeast,18903.49141 1126 | 23,female,42.75,1,yes,northeast,40904.1995 1127 | 63,female,25.08,0,no,northwest,14254.6082 1128 | 55,male,29.9,0,no,southwest,10214.636 1129 | 35,female,35.86,2,no,southeast,5836.5204 1130 | 34,male,32.8,1,no,southwest,14358.36437 1131 | 19,female,18.6,0,no,southwest,1728.897 1132 | 39,female,23.87,5,no,southeast,8582.3023 1133 | 27,male,45.9,2,no,southwest,3693.428 1134 | 57,male,40.28,0,no,northeast,20709.02034 1135 | 52,female,18.335,0,no,northwest,9991.03765 1136 | 28,male,33.82,0,no,northwest,19673.33573 1137 | 50,female,28.12,3,no,northwest,11085.5868 1138 | 44,female,25,1,no,southwest,7623.518 1139 | 26,female,22.23,0,no,northwest,3176.2877 1140 | 33,male,30.25,0,no,southeast,3704.3545 1141 | 19,female,32.49,0,yes,northwest,36898.73308 1142 | 50,male,37.07,1,no,southeast,9048.0273 1143 | 41,female,32.6,3,no,southwest,7954.517 1144 | 52,female,24.86,0,no,southeast,27117.99378 1145 | 39,male,32.34,2,no,southeast,6338.0756 1146 | 50,male,32.3,2,no,southwest,9630.397 1147 | 52,male,32.775,3,no,northwest,11289.10925 1148 | 60,male,32.8,0,yes,southwest,52590.82939 1149 | 20,female,31.92,0,no,northwest,2261.5688 1150 | 55,male,21.5,1,no,southwest,10791.96 1151 | 42,male,34.1,0,no,southwest,5979.731 1152 | 18,female,30.305,0,no,northeast,2203.73595 1153 | 58,female,36.48,0,no,northwest,12235.8392 1154 | 43,female,32.56,3,yes,southeast,40941.2854 1155 | 35,female,35.815,1,no,northwest,5630.45785 1156 | 48,female,27.93,4,no,northwest,11015.1747 1157 | 36,female,22.135,3,no,northeast,7228.21565 1158 | 19,male,44.88,0,yes,southeast,39722.7462 1159 | 23,female,23.18,2,no,northwest,14426.07385 1160 | 20,female,30.59,0,no,northeast,2459.7201 1161 | 32,female,41.1,0,no,southwest,3989.841 1162 | 43,female,34.58,1,no,northwest,7727.2532 1163 | 34,male,42.13,2,no,southeast,5124.1887 1164 | 30,male,38.83,1,no,southeast,18963.17192 1165 | 18,female,28.215,0,no,northeast,2200.83085 1166 | 41,female,28.31,1,no,northwest,7153.5539 1167 | 35,female,26.125,0,no,northeast,5227.98875 1168 | 57,male,40.37,0,no,southeast,10982.5013 1169 | 29,female,24.6,2,no,southwest,4529.477 1170 | 32,male,35.2,2,no,southwest,4670.64 1171 | 37,female,34.105,1,no,northwest,6112.35295 1172 | 18,male,27.36,1,yes,northeast,17178.6824 1173 | 43,female,26.7,2,yes,southwest,22478.6 1174 | 56,female,41.91,0,no,southeast,11093.6229 1175 | 38,male,29.26,2,no,northwest,6457.8434 1176 | 29,male,32.11,2,no,northwest,4433.9159 1177 | 22,female,27.1,0,no,southwest,2154.361 1178 | 52,female,24.13,1,yes,northwest,23887.6627 1179 | 40,female,27.4,1,no,southwest,6496.886 1180 | 23,female,34.865,0,no,northeast,2899.48935 1181 | 31,male,29.81,0,yes,southeast,19350.3689 1182 | 42,female,41.325,1,no,northeast,7650.77375 1183 | 24,female,29.925,0,no,northwest,2850.68375 1184 | 25,female,30.3,0,no,southwest,2632.992 1185 | 48,female,27.36,1,no,northeast,9447.3824 1186 | 23,female,28.49,1,yes,southeast,18328.2381 1187 | 45,male,23.56,2,no,northeast,8603.8234 1188 | 20,male,35.625,3,yes,northwest,37465.34375 1189 | 62,female,32.68,0,no,northwest,13844.7972 1190 | 43,female,25.27,1,yes,northeast,21771.3423 1191 | 23,female,28,0,no,southwest,13126.67745 1192 | 31,female,32.775,2,no,northwest,5327.40025 1193 | 41,female,21.755,1,no,northeast,13725.47184 1194 | 58,female,32.395,1,no,northeast,13019.16105 1195 | 48,female,36.575,0,no,northwest,8671.19125 1196 | 31,female,21.755,0,no,northwest,4134.08245 1197 | 19,female,27.93,3,no,northwest,18838.70366 1198 | 19,female,30.02,0,yes,northwest,33307.5508 1199 | 41,male,33.55,0,no,southeast,5699.8375 1200 | 40,male,29.355,1,no,northwest,6393.60345 1201 | 31,female,25.8,2,no,southwest,4934.705 1202 | 37,male,24.32,2,no,northwest,6198.7518 1203 | 46,male,40.375,2,no,northwest,8733.22925 1204 | 22,male,32.11,0,no,northwest,2055.3249 1205 | 51,male,32.3,1,no,northeast,9964.06 1206 | 18,female,27.28,3,yes,southeast,18223.4512 1207 | 35,male,17.86,1,no,northwest,5116.5004 1208 | 59,female,34.8,2,no,southwest,36910.60803 1209 | 36,male,33.4,2,yes,southwest,38415.474 1210 | 37,female,25.555,1,yes,northeast,20296.86345 1211 | 59,male,37.1,1,no,southwest,12347.172 1212 | 36,male,30.875,1,no,northwest,5373.36425 1213 | 39,male,34.1,2,no,southeast,23563.01618 1214 | 18,male,21.47,0,no,northeast,1702.4553 1215 | 52,female,33.3,2,no,southwest,10806.839 1216 | 27,female,31.255,1,no,northwest,3956.07145 1217 | 18,male,39.14,0,no,northeast,12890.05765 1218 | 40,male,25.08,0,no,southeast,5415.6612 1219 | 29,male,37.29,2,no,southeast,4058.1161 1220 | 46,female,34.6,1,yes,southwest,41661.602 1221 | 38,female,30.21,3,no,northwest,7537.1639 1222 | 30,female,21.945,1,no,northeast,4718.20355 1223 | 40,male,24.97,2,no,southeast,6593.5083 1224 | 50,male,25.3,0,no,southeast,8442.667 1225 | 20,female,24.42,0,yes,southeast,26125.67477 1226 | 41,male,23.94,1,no,northeast,6858.4796 1227 | 33,female,39.82,1,no,southeast,4795.6568 1228 | 38,male,16.815,2,no,northeast,6640.54485 1229 | 42,male,37.18,2,no,southeast,7162.0122 1230 | 56,male,34.43,0,no,southeast,10594.2257 1231 | 58,male,30.305,0,no,northeast,11938.25595 1232 | 52,male,34.485,3,yes,northwest,60021.39897 1233 | 20,female,21.8,0,yes,southwest,20167.33603 1234 | 54,female,24.605,3,no,northwest,12479.70895 1235 | 58,male,23.3,0,no,southwest,11345.519 1236 | 45,female,27.83,2,no,southeast,8515.7587 1237 | 26,male,31.065,0,no,northwest,2699.56835 1238 | 63,female,21.66,0,no,northeast,14449.8544 1239 | 58,female,28.215,0,no,northwest,12224.35085 1240 | 37,male,22.705,3,no,northeast,6985.50695 1241 | 25,female,42.13,1,no,southeast,3238.4357 1242 | 52,male,41.8,2,yes,southeast,47269.854 1243 | 64,male,36.96,2,yes,southeast,49577.6624 1244 | 22,female,21.28,3,no,northwest,4296.2712 1245 | 28,female,33.11,0,no,southeast,3171.6149 1246 | 18,male,33.33,0,no,southeast,1135.9407 1247 | 28,male,24.3,5,no,southwest,5615.369 1248 | 45,female,25.7,3,no,southwest,9101.798 1249 | 33,male,29.4,4,no,southwest,6059.173 1250 | 18,female,39.82,0,no,southeast,1633.9618 1251 | 32,male,33.63,1,yes,northeast,37607.5277 1252 | 24,male,29.83,0,yes,northeast,18648.4217 1253 | 19,male,19.8,0,no,southwest,1241.565 1254 | 20,male,27.3,0,yes,southwest,16232.847 1255 | 40,female,29.3,4,no,southwest,15828.82173 1256 | 34,female,27.72,0,no,southeast,4415.1588 1257 | 42,female,37.9,0,no,southwest,6474.013 1258 | 51,female,36.385,3,no,northwest,11436.73815 1259 | 54,female,27.645,1,no,northwest,11305.93455 1260 | 55,male,37.715,3,no,northwest,30063.58055 1261 | 52,female,23.18,0,no,northeast,10197.7722 1262 | 32,female,20.52,0,no,northeast,4544.2348 1263 | 28,male,37.1,1,no,southwest,3277.161 1264 | 41,female,28.05,1,no,southeast,6770.1925 1265 | 43,female,29.9,1,no,southwest,7337.748 1266 | 49,female,33.345,2,no,northeast,10370.91255 1267 | 64,male,23.76,0,yes,southeast,26926.5144 1268 | 55,female,30.5,0,no,southwest,10704.47 1269 | 24,male,31.065,0,yes,northeast,34254.05335 1270 | 20,female,33.3,0,no,southwest,1880.487 1271 | 45,male,27.5,3,no,southwest,8615.3 1272 | 26,male,33.915,1,no,northwest,3292.52985 1273 | 25,female,34.485,0,no,northwest,3021.80915 1274 | 43,male,25.52,5,no,southeast,14478.33015 1275 | 35,male,27.61,1,no,southeast,4747.0529 1276 | 26,male,27.06,0,yes,southeast,17043.3414 1277 | 57,male,23.7,0,no,southwest,10959.33 1278 | 22,female,30.4,0,no,northeast,2741.948 1279 | 32,female,29.735,0,no,northwest,4357.04365 1280 | 39,male,29.925,1,yes,northeast,22462.04375 1281 | 25,female,26.79,2,no,northwest,4189.1131 1282 | 48,female,33.33,0,no,southeast,8283.6807 1283 | 47,female,27.645,2,yes,northwest,24535.69855 1284 | 18,female,21.66,0,yes,northeast,14283.4594 1285 | 18,male,30.03,1,no,southeast,1720.3537 1286 | 61,male,36.3,1,yes,southwest,47403.88 1287 | 47,female,24.32,0,no,northeast,8534.6718 1288 | 28,female,17.29,0,no,northeast,3732.6251 1289 | 36,female,25.9,1,no,southwest,5472.449 1290 | 20,male,39.4,2,yes,southwest,38344.566 1291 | 44,male,34.32,1,no,southeast,7147.4728 1292 | 38,female,19.95,2,no,northeast,7133.9025 1293 | 19,male,34.9,0,yes,southwest,34828.654 1294 | 21,male,23.21,0,no,southeast,1515.3449 1295 | 46,male,25.745,3,no,northwest,9301.89355 1296 | 58,male,25.175,0,no,northeast,11931.12525 1297 | 20,male,22,1,no,southwest,1964.78 1298 | 18,male,26.125,0,no,northeast,1708.92575 1299 | 28,female,26.51,2,no,southeast,4340.4409 1300 | 33,male,27.455,2,no,northwest,5261.46945 1301 | 19,female,25.745,1,no,northwest,2710.82855 1302 | 45,male,30.36,0,yes,southeast,62592.87309 1303 | 62,male,30.875,3,yes,northwest,46718.16325 1304 | 25,female,20.8,1,no,southwest,3208.787 1305 | 43,male,27.8,0,yes,southwest,37829.7242 1306 | 42,male,24.605,2,yes,northeast,21259.37795 1307 | 24,female,27.72,0,no,southeast,2464.6188 1308 | 29,female,21.85,0,yes,northeast,16115.3045 1309 | 32,male,28.12,4,yes,northwest,21472.4788 1310 | 25,female,30.2,0,yes,southwest,33900.653 1311 | 41,male,32.2,2,no,southwest,6875.961 1312 | 42,male,26.315,1,no,northwest,6940.90985 1313 | 33,female,26.695,0,no,northwest,4571.41305 1314 | 34,male,42.9,1,no,southwest,4536.259 1315 | 19,female,34.7,2,yes,southwest,36397.576 1316 | 30,female,23.655,3,yes,northwest,18765.87545 1317 | 18,male,28.31,1,no,northeast,11272.33139 1318 | 19,female,20.6,0,no,southwest,1731.677 1319 | 18,male,53.13,0,no,southeast,1163.4627 1320 | 35,male,39.71,4,no,northeast,19496.71917 1321 | 39,female,26.315,2,no,northwest,7201.70085 1322 | 31,male,31.065,3,no,northwest,5425.02335 1323 | 62,male,26.695,0,yes,northeast,28101.33305 1324 | 62,male,38.83,0,no,southeast,12981.3457 1325 | 42,female,40.37,2,yes,southeast,43896.3763 1326 | 31,male,25.935,1,no,northwest,4239.89265 1327 | 61,male,33.535,0,no,northeast,13143.33665 1328 | 42,female,32.87,0,no,northeast,7050.0213 1329 | 51,male,30.03,1,no,southeast,9377.9047 1330 | 23,female,24.225,2,no,northeast,22395.74424 1331 | 52,male,38.6,2,no,southwest,10325.206 1332 | 57,female,25.74,2,no,southeast,12629.1656 1333 | 23,female,33.4,0,no,southwest,10795.93733 1334 | 52,female,44.7,3,no,southwest,11411.685 1335 | 50,male,30.97,3,no,northwest,10600.5483 1336 | 18,female,31.92,0,no,northeast,2205.9808 1337 | 18,female,36.85,0,no,southeast,1629.8335 1338 | 21,female,25.8,0,no,southwest,2007.945 1339 | 61,female,29.07,0,yes,northwest,29141.3603 1340 | --------------------------------------------------------------------------------