Feature Selection in MATLAB

Question

I have a dataset for text classification ready to be used in MATLAB. Each document is a vector in this dataset and the dimensionality of this vector is extremely high. In th

Answer 1

MATLAB (and its toolboxes) include a number of functions that deal with feature selection:

• RANDFEATURES (Bioinformatics Toolbox): Generate randomized subset of features directed by a classifier
• RANKFEATURES (Bioinformatics Toolbox): Rank features by class separability criteria
• SEQUENTIALFS (Statistics Toolbox): Sequential feature selection
• RELIEFF (Statistics Toolbox): Relief-F algorithm
• TREEBAGGER.OOBPermutedVarDeltaError, predictorImportance (Statistics Toolbox): Using ensemble methods (bagged decision trees)

You can also find examples that demonstrates usage on real datasets:

• Identifying Significant Features and Classifying Protein Profiles
• Genetic Algorithm Search for Features in Mass Spectrometry Data

In addition, there exist third-party toolboxes:

• Matlab Toolbox for Dimensionality Reduction
• LIBGS: A MATLAB Package for Gene Selection

Otherwise you can always call your favorite functions from WEKA directly from MATLAB since it include a JVM...