Input Feature Selection Method Based on Feature Set Equivalence and Mutual Information Gain Maximization

Input Feature Selection Method Based on Feature Set Equivalence and Mutual Information Gain Maximization

Feature selection is the first and essential step for dimension reduction in many application areas, such as data mining and machine learning, due to its computational efficiency and interpretability of the results. This paper focuses on feature selection methods based on information theory. By stud...

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Bibliographic Details
Main Authors: Xinzheng Wang, Bing Guo, Yan Shen, Chimin Zhou, Xuliang Duan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Feature selection
mutual Information
equivalent partition
Online Access:https://ieeexplore.ieee.org/document/8873578/

Internet

https://ieeexplore.ieee.org/document/8873578/

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