Ensemble-based classifiers

Lior Rokach

doi:10.1007/s10462-009-9124-7

Ensemble-based classifiers

Lior Rokach

Department of Software and Information Systems Engineering

Research output: Contribution to journal › Article › peer-review

2160 Scopus citations

Abstract

The idea of ensemble methodology is to build a predictive model by integrating multiple models. It is well-known that ensemble methods can be used for improving prediction performance. Researchers from various disciplines such as statistics and AI considered the use of ensemble methodology. This paper, review existing ensemble techniques and can be served as a tutorial for practitioners who are interested in building ensemble based systems.

Original language	English
Pages (from-to)	1-39
Number of pages	39
Journal	Artificial Intelligence Review
Volume	33
Issue number	1-2
DOIs	https://doi.org/10.1007/s10462-009-9124-7
State	Published - 1 Feb 2010

Keywords

Boosting
Classification
Ensemble of classifiers
Supervised learning

ASJC Scopus subject areas

Language and Linguistics
Linguistics and Language
Artificial Intelligence

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10.1007/s10462-009-9124-7

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abstract = "The idea of ensemble methodology is to build a predictive model by integrating multiple models. It is well-known that ensemble methods can be used for improving prediction performance. Researchers from various disciplines such as statistics and AI considered the use of ensemble methodology. This paper, review existing ensemble techniques and can be served as a tutorial for practitioners who are interested in building ensemble based systems.",

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Ensemble-based classifiers

Abstract

Keywords

ASJC Scopus subject areas

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