Non-uniform layered clustering for ensemble classifier generation and optimality

Ashfaqur RAHMAN, Brijesh VERMA, Xin YAO

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

11 Citations (Scopus)


In this paper we present an approach to generate ensemble of classifiers using non-uniform layered clustering. In the proposed approach the dataset is partitioned into variable number of clusters at different layers. A set of base classifiers is trained on the clusters at different layers. The decision on a pattern at each layer is obtained from the classifier trained on the nearest cluster and the decisions from the different layers are fused using majority voting to obtain the final verdict. The proposed approach provides a mechanism to obtain the optimal number of layers and clusters using a Genetic Algorithm. Clustering identifies difficult-to-classify patterns and layered non-uniform clustering approach brings in diversity among the base classifiers at different layers. The proposed method performs relatively better than the other state-of-art ensemble classifier generation methods as evidenced from the experimental results. © 2010 Springer-Verlag.
Original languageEnglish
Title of host publicationNeural Information Processing. Theory and Algorithms : 17th International Conference, ICONIP 2010, Sydney, Australia, November 21-25, 2010, Proceedings, Part I
EditorsKok Wai WONG, B. Sumudu U. MENDIS, Abdesselam BOUZERDOUM
PublisherSpringer Berlin Heidelberg
Number of pages8
ISBN (Electronic)978364217537
ISBN (Print)9783642175367
Publication statusPublished - 2010
Externally publishedYes
Event17th International Conference on Neural Information Processing, ICONIP 2010 - Sydney, Australia
Duration: 21 Nov 201025 Nov 2010

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin, Heidelberg
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Neural Information Processing, ICONIP 2010


  • ensemble classifier
  • genetic algorithm
  • optimal clustering


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