Tools for Information-Based Feature Selection and Scoring
Minimal normalised joint mutual information maximisation filter
Double input symmetrical relevance filter
Join factors
Conditional mutual information maximisation filter
Minimal conditional mutual information maximisation filter
Conditional mutual information matrix with a common condition
Conditional mutual information scores
Directional normalised mutual information matrix
Entropy scores
Conditional mutual information matrix with a common variable
Gini impurity scores
Joint entropy scores
Joint impurity filter
Joint mutual information filter
Third-order joint mutual information filter
Minimal joint mutual information maximisation filter
Joint mutual information matrix
Joint mutual information scores
Inverse Kendall transform
Kendall transformation
Maximal pairwise conditional mutual information scores
Maximal pairwise joint mutual information scores
Mutual information scores
Mutual information maximisation filter
Mutual information matrix
Minimal pairwise conditional mutual information scores
Extreme values of pairwise conditional mutual information scores
Minimum redundancy maximal relevancy filter
Normalised joint mutual information matrix
Normalised joint mutual information scores
Normalised mutual information matrix
Tools for information-based feature selection and scoring
Mutual information of feature triples
Top-scoring pairs transformation
A toolbox of fast, native and parallel implementations of various information-based importance criteria estimators and feature selection filters based on them, inspired by the overview by Brown, Pocock, Zhao and Lujan (2012) <https://www.jmlr.org/papers/v13/brown12a.html>. Contains, among other, minimum redundancy maximal relevancy ('mRMR') method by Peng, Long and Ding (2005) <doi:10.1109/TPAMI.2005.159>; joint mutual information ('JMI') method by Yang and Moody (1999) <https://papers.nips.cc/paper/1779-data-visualization-and-feature-selection-new-algorithms-for-nongaussian-data>; double input symmetrical relevance ('DISR') method by Meyer and Bontempi (2006) <doi:10.1007/11732242_9> as well as joint mutual information maximisation ('JMIM') method by Bennasar, Hicks and Setchi (2015) <doi:10.1016/j.eswa.2015.07.007>.