Optimizing stacking ensemble by an ant colony optimization approach

Yijun CHEN, Man Leung WONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

10 Citations (Scopus)

Abstract

An ensemble is a collective decision making system which applies some strategy to combine the predictions of classifiers to generate its prediction on new instances. Stacking is a well-known approach among the ensembles. It is not easy to find a suitable ensemble configuration for a specific dataset. Ant Colony Optimization (ACO) is a popular metaheuristic approach which could be a solution to find configurations. In this work, we propose a new Stacking construction method which applies ACO in the Stacking construction process to generate domain-specific configurations. The experiment results show that the new approach can achieve promising results on 18 datasets compared with some well-known ensemble approaches.
Original languageEnglish
Title of host publicationGenetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication
Pages7-8
Number of pages2
DOIs
Publication statusPublished - 1 Jan 2011

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Keywords

  • aco
  • ensemble
  • metaheuristics
  • stacking

Cite this

CHEN, Y., & WONG, M. L. (2011). Optimizing stacking ensemble by an ant colony optimization approach. In Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication (pp. 7-8) https://doi.org/10.1145/2001858.2001863