HOFS: Higher order mutual information approximation for feature selection in R

HOFS: Higher order mutual information approximation for feature selection in R

Feature selection is a process of choosing a subset of relevant features so that the quality of predictive models can be improved. An extensive body of work exists on information-theoretic feature selection, based on maximizing Mutual Information (MI) between subsets of features and class labels. Th...

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Bibliographic Details
Main Authors: Krzysztof Gajowniczek, Jialin Wu, Soumyajit Gupta, Chandrajit Bajaj
Format: Article
Language:English
Published: Elsevier 2022-07-01
Series:SoftwareX
Subjects:
Feature selection
Machine learning
Mutual information
Higher order approximation
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711022000930

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http://www.sciencedirect.com/science/article/pii/S2352711022000930

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