Feature selection

Mrmr feature selection (using mutual information computation) in matlab

The following Matlab project contains the source code and Matlab examples used for mrmr feature selection (using mutual information computation). This package is the mRMR (minimum-redundancy maximum-relevancy) feature selection method in (Peng et al, 2005 and Ding & Peng, 2005, 2003), whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent publications.

Minimum redundancy maximum relevance feature selection in matlab

The following Matlab project contains the source code and Matlab examples used for minimum redundancy maximum relevance feature selection. Two source code files of the mRMR (minimum-redundancy maximum-relevancy) feature selection method in (Peng et al, 2005 and Ding & Peng, 2005, 2003), whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent publications.

Feature selection based on interaction information in matlab

The following Matlab project contains the source code and Matlab examples used for feature selection based on interaction information. This is a self-contained package for running feature selection filters: Given a (usually large) number of noisy and partly redundant variables and a target choose a small but indicative subset as input to a classification or regression technique.

Feature selection using matlab

The following Matlab project contains the source code and Matlab examples used for feature selection using matlab. The DEMO includes 5 feature selection algorithms: • Sequential Forward Selection (SFS) • Sequential Floating Forward Selection (SFFS) • Sequential Backward Selection (SBS) • Sequential Floating Backward Selection (SFBS) • ReliefF Two CCR estimation methods: • Cross-validation • Resubstitution After selecting the best feature subset, the classifier obtained can be used for classifying any pattern.

Information theoretic feature selection in matlab

The following Matlab project contains the source code and Matlab examples used for information theoretic feature selection. Description: Code (Matlab/C++ Mex) for the following MI based feature selection approaches: - Maximum relevance (maxRel) - Minimum redundancy maximum relevance (MRMR) - Minimum redundancy (minRed) - Quadratic programming feature selection (QPFS) - Mutual information quotient (MIQ) - Maximum relevance minimum total redundancy (MRMTR) or extended MRMR (EMRMR) - Spectral relaxation global Conditional Mutual Information (SPEC_CMI)
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