├── README.md └── LICENSE.md /README.md: -------------------------------------------------------------------------------- 1 | # mvdata 2 | 3 | Data sets for multi-view learning in MatLab ".mat" file format. 4 | 5 | ##Introduction 6 | 7 | This repository contains the data that is used in the following paper. 8 | >Li, Yeqing, Feiping Nie, Heng Huang, and Junzhou Huang. "Large-Scale Multi-View Spectral Clustering via Bipartite Graph." In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. 2015. 9 | 10 | If you use the data, please cite our paper: 11 | 12 | @inproceedings{li2015large, 13 | title={Large-Scale Multi-View Spectral Clustering via Bipartite Graph}, 14 | author={Li, Yeqing and Nie, Feiping and Huang, Heng and Huang, Junzhou}, 15 | booktitle={Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence}, 16 | year={2015} 17 | } 18 | 19 | ###How to use 20 | 21 | Download from google drive using the browser. 22 | 23 | + https://drive.google.com/drive/folders/1O_3YmthAZGiq1ZPSdE74R7Nwos2PmnHH 24 | 25 | 26 | **Note**: The whole dataset is about 300MB to 400MB. 27 | 28 | ###About the data format 29 | 30 | All the data is stored in MatLab ".mat" file format. Each ".mat" file contains at least two variables: X and Y. "X" is a cell array of feature matrix (dimension N by d) and "Y" is the label vector (dimension N by 1), where N is the number of data points and d is the dimension of features. 31 | The specification of the data is listed below 32 | 33 | | No. | Handwritten | Caltech-7/20 | Reuters | NUS-WIDE | AWA | 34 | |----------------|-------------|---------------|----------------|-----------|--------------| 35 | | 1 | Pix(240) | Gabor(48) | English(21531) | CH(65) | CQ(2688) | 36 | | 2 | Fou(76) | WM(40) | France(24892) | CM(226) | LSS(2000) | 37 | | 3 | Fac(216) | CENTRIST(254) | German(34251) | CORR(145) | PHOG(252) | 38 | | 4 | ZER(47) | HOG(1984) | Italian(15506) | EDH(74) | SIFT(2000) | 39 | | 5 | KAR(64) | GIST(512) | Spanish(11547) | WT(129) | RGSIFT(2000) | 40 | | 6 | MOR(6) | LBP(928) | - | - | SURF(2000) | 41 | | num of data | 2000 | 1474/2386 | 18758 | 26315 | 4000 | 42 | | num of classes | 10 | 7/20 | 6 | 31 | 50 | 43 | 44 | **Note**: Caltech-7 and Caltech-20 are two subsets of Caltech-101, which contains only 7 and 20 classes respectively. The creation of these subsets is due to the unbalance of the number of data in each classes of Caltech-101. 45 | 46 | List of features: 47 | 48 | - Fourier coefficients of the character shapes (FOU) 49 | - Profile correlations (FAC) 50 | - Pixel averages in 2 × 3 windows (Pix), 51 | - Zernike moment (ZER) 52 | - Morphological (MOR) features. 53 | - Gabor feature 54 | - Wavelet moments (WM) 55 | - CENTRIST feature 56 | - Histogram of oriented gradients (HOG) feature 57 | - GIST feature 58 | - Local binary patterns (LBP) feature 59 | - Color Histogram (CH) 60 | - Color moments (CM) 61 | - Color correlation (CORR) 62 | - Edge distribution (EDH) 63 | - Wavelet texture (WT) 64 | 65 | ##Source 66 | 67 | The source of the data are downloaded from the following links: 68 | 69 | - [Handwritten](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) 70 | - [Caltech-101](http://www.vision.caltech.edu/Image_Datasets/Caltech101/) 71 | - [Reuters](https://archive.ics.uci.edu/ml/datasets.html) 72 | - [NUS-WIDE-Object](http://lms.comp.nus.edu.sg/research/NUS-WIDE.htm) 73 | - [Animal with attributes (AWA)](http://attributes.kyb.tuebingen.mpg.de/) 74 | 75 | 76 | -------------------------------------------------------------------------------- /LICENSE.md: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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