Classifier ensemble selection using hybrid genetic algorithms

Young Won Kim; Il Seok Oh

doi:10.1016/j.patrec.2007.12.013

Classifier ensemble selection using hybrid genetic algorithms

Young Won Kim
, Il Seok Oh^*

^*Corresponding author for this work

Electronics and Telecommunications Research Institute

Research output: Contribution to journal › Journal article › peer-review

30 Scopus citations

Abstract

This paper proposes a hybrid genetic algorithm for classifier ensemble selection. In this paper, two local search operations used to improve offspring prior to replacement are proposed. The operations are parameterized in order to control the computation time. Experimental results and statistical tests demonstrate the effectiveness of the proposed hybrid genetic algorithm and related local search operations.

Original language	English
Pages (from-to)	796-802
Number of pages	7
Journal	Pattern Recognition Letters
Volume	29
Issue number	6
DOIs	https://doi.org/10.1016/j.patrec.2007.12.013
State	Published - 2008.04.15

Keywords

Ensemble selection
Genetic algorithm
Local search operation
Multiple classifier combination

Quacquarelli Symonds(QS) Subject Topics

Computer Science & Information Systems
Data Science

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10.1016/j.patrec.2007.12.013

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title = "Classifier ensemble selection using hybrid genetic algorithms",

abstract = "This paper proposes a hybrid genetic algorithm for classifier ensemble selection. In this paper, two local search operations used to improve offspring prior to replacement are proposed. The operations are parameterized in order to control the computation time. Experimental results and statistical tests demonstrate the effectiveness of the proposed hybrid genetic algorithm and related local search operations.",

keywords = "Ensemble selection, Genetic algorithm, Local search operation, Multiple classifier combination",

author = "Kim, \{Young Won\} and Oh, \{Il Seok\}",

year = "2008",

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language = "English",

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journal = "Pattern Recognition Letters",

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T1 - Classifier ensemble selection using hybrid genetic algorithms

AU - Kim, Young Won

AU - Oh, Il Seok

PY - 2008/4/15

Y1 - 2008/4/15

N2 - This paper proposes a hybrid genetic algorithm for classifier ensemble selection. In this paper, two local search operations used to improve offspring prior to replacement are proposed. The operations are parameterized in order to control the computation time. Experimental results and statistical tests demonstrate the effectiveness of the proposed hybrid genetic algorithm and related local search operations.

AB - This paper proposes a hybrid genetic algorithm for classifier ensemble selection. In this paper, two local search operations used to improve offspring prior to replacement are proposed. The operations are parameterized in order to control the computation time. Experimental results and statistical tests demonstrate the effectiveness of the proposed hybrid genetic algorithm and related local search operations.

KW - Ensemble selection

KW - Genetic algorithm

KW - Local search operation

KW - Multiple classifier combination

UR - https://www.scopus.com/pages/publications/40149107260

U2 - 10.1016/j.patrec.2007.12.013

DO - 10.1016/j.patrec.2007.12.013

M3 - Journal article

AN - SCOPUS:40149107260

SN - 0167-8655

VL - 29

SP - 796

EP - 802

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 6

ER -

Classifier ensemble selection using hybrid genetic algorithms

Abstract

Keywords

Quacquarelli Symonds(QS) Subject Topics

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