Feature Selection Library (FSLib) is a widely applicable MATLAB library for
Feature Selection (FS). FS is an essential component of machine learning and
data mining which has been studied for many years under many different
conditions and in diverse scenarios. These algorithms aim at ranking and
selecting a subset of relevant features according to their degrees of
relevance, preference, or importance as defined in a specific application.
Because feature selection can reduce the amount of features used for training
classification models, it alleviates the effect of the curse of dimensionality,
speeds up the learning process, improves model's performance, and enhances data
understanding. This short report provides an overview of the feature selection
algorithms included in the FSLib MATLAB toolbox among filter, embedded, and
wrappers methods.Comment: Feature Selection Library (FSLib) 201