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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Expert systems with applications Ročník 174; s. 114765
Hlavní autori:	Odhiambo Omuya, Erick, Onyango Okeyo, George, Waema Kimwele, Michael
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Ltd 15.07.2021 Elsevier BV
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!