Hi, my name is Yifeng Li. I am sharing my studies on regularized linear models and kernel approaches with you. I name this toolbox as RLMK Toolbox. You can find a tutorial on linear models regularized by various regularization terms. Many loss functions are investigated. Of course, this includes the main variants of support vector machines (SVMs). I have implemented the most important linear models in my toolbox. I will further implement more models. The following are the current functionality:
You can download the tutorial and source code from Tutorial and Source Code. Please cite it properly if you use the content of the tutorial and the source code in your publications. If you find any bugs, missing files, please let me know. If you have any suggestions and contributions to this tutorial and toolbox, I would be very happy to speak with you.
You may be also interested in my
Non-Negative Matrix Factorization toolbox at https://sites.google.com/site/nmftool,
Sparse Representation toolbox at https://sites.google.com/site/sparsereptool,
Regularized Linear Models and Kernels toolbox: https://sites.google.com/site/rlmktool,
Probabilistic Graphical Models toolbox at https://sites.google.com/site/pgmtool,
Spectral Clustering toolbox at https://sites.google.com/site/speclust.
Citations:
Yifeng Li, "Regularized linear models: theories and implementations", in "Sparse Machine Learning Models in Bioinformatics", PhD Thesis, School of Computer Science, University of Windsor, 2013. Thesis Available at http://scholar.uwindsor.ca/etd/5023/
My contact information:
Yifeng Li
https://sites.google.com/site/yifengliresearch
Centre for Molecular Medicine and Therapeutics
Department of Medical Genetics
University of British Columbia
Vancouver, BC, Canada
Email: yifeng.li.cn{at}gmail.com and li11112c{at}uwindsor.ca
You can also contact my previous supervisor: Dr. Alioune Ngom.