Feature subset selection by gravitational search algorithm optimization

A new method for feature subset selection in machine learning, FSS-MGSA (Feature Subset Selection by Modified Gravitational Search Algorithm), is presented. FSS-MGSA is an evolutionary, stochastic search algorithm based on the law of gravity and mass interactions, and it can be executed when domain...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Information sciences Jg. 281; S. 128 - 146
Hauptverfasser:	Han, XiaoHong, Chang, XiaoMing, Quan, Long, Xiong, XiaoYan, Li, JingXia, Zhang, ZhaoXia, Liu, Yi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 10.10.2014
Schlagworte:	Algorithms Biological diversity Chaos theory Chaotic map Classification Evolutionary Feature subset selection Genetic algorithms Gravitational search algorithm Learning algorithm MAP (programming language) Optimization Search algorithms Sequential quadratic programming Feature subset selection Gravitational search algorithm Chaotic map Sequential quadratic programming Learning algorithm Classification
ISSN:	0020-0255, 1872-6291
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!