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Introduction: This is the multi-view matrix factorization (MVMF) package in Python 2.7 devloped by Yifeng Li with NRC, Ottawa. Version: 1.2 Depencency: numpy, scipy, matplotlib. Installation: (0. Install DECRES (https://github.com/yifeng-li/DECRES) for calling the implemented classifiers.) 1. Download MVMF from github. 2. Uncompress it to your local machine, say YOUR_PATH/mvmf_v1_2. 3. Add "export PYTHONPATH=$PYTHONPATH:YOUR_PATH/mvmf_v1_2" to your .bashrc. Models: 1. Multi-class non-negative matrix factorization (MC-NMF): mcnmf.py. 2. Multi-class non-negative matrix factorization with stability selection (SS-MC-NMF): ssmcnmf.py. 3. Automatic relavent determination non-negative matrix factorization (ARD-NMF): ardnmf.py. 4. Variational non-negative matrix factorization models (variational NMF): vnmf.py. 5. I am designing multi-view non-negative matrix factorization models for multi-feature-set data. Stay tuned! Data: 1. Simulated data are available in ./data of this package; Data generator are available in this package too. 2. Multi-tumor RNA-seq data are too big to upload. Please request it directly from Yifeng. Examples: 1. main_mcnmf_sim.py: Example of how to use MC-NMF on the simulated data. 2. main_ssmcnmf_sim.py: Example of how to use SS-MC-NMF on the simulated data. 3. main_mcnmf_rnaseq.py: Example of how to use MC-NMF on the multi-tumor RNA-seq data. 4. main_ssmcnmf_rnaseq.py: Example of how to use SS-MC-NMF on the multi-tumor RNA-seq data. References: [1] Yifeng Li, Youlian Pan and Ziying Liu, "Multi-class non-negative matrix factorization for feature pattern discovery," Aug. 2016, submitted. [2] Yifeng Li, "Advances in multi-view matrix factorizations," 2016 International Joint Conference on Neural Networks (IJCNN/WCCI), Vancouver, Canada, July 2016, pp. 3793-3800. [3] Yifeng Li, Fangxiang Wu, and Alioune Ngom, "A review on machine learning principles for multi-view biological data integration," Briefings in Bioinformatics, accepted on Oct 14, 2016. Contact: Yifeng Li, PhD Research Officer Information and Communications Technologies National Research Council Canada Email_1: yifeng.li@nrc-cnrc.gc.ca Email_2: yifeng.li.cn@gmail.com
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Multi-view matrix factorization models for integrative data analysis.
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