Hybrid Binary Bat Algorithm with Cross-Entropy Method for Feature Selection

Feature selection aims to find an optimal subset from a given set of features. As this task can be seen as a challenging combinatorial optimization problem while the classical optimization techniques have some limitations in solving it. In this paper we propose a novel hybrid metaheuristic, improved...

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Veröffentlicht in:	2019 4th International Conference on Control and Robotics Engineering (ICCRE) S. 165 - 169
Hauptverfasser:	Li, Guocheng, Le, Chengyi
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.04.2019
Schlagworte:	bat algorithm Classification algorithms co-evolution cross-entropy method Entropy Feature extraction feature selection Genetic algorithms hybrid optimization Optimization Sociology Statistics
Online-Zugang:	Volltext
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