Feature Selection for Classification using Principal Component Analysis and Information Gain

•Feature selection improves performance of machine learning algorithms.•Feature selection with more n-tier techniques is simpler and more stable.•A feature selection model that is not specific to any data set is widely applied. Feature Selection and classification have previously been widely applied...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 174; p. 114765
Main Authors:	Odhiambo Omuya, Erick, Onyango Okeyo, George, Waema Kimwele, Michael
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 15.07.2021 Elsevier BV
Subjects:	Algorithms Classification Data mining Dimensionality reduction Feature selection Filter model Information gain Machine learning Principal component analysis Principal components analysis Dimensionality reduction Feature selection Filter model Information gain Classification Principal component analysis
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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