Voting-XCSc: A consensus clustering method via learning classifier system

Liqiang Qian, Yinghuan Shi, Yang Gao, Hujun Yin

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    In this article, a novel consensus clustering method (voting-XCSc) via learning classifier system is proposed, which aims (1) to automatically determine the clustering number and (2) to achieve consensus results by reducing the influence coming from the randomness. When conducting the clustering for the data points, the proposed voting-XCSc will first employ the XCSc to generate a set of clustering results with different clustering numbers, and then it will adopt the dissociation-based strategy to experimentally determine the clustering number among all the candidates. Finally, a majority voting-based consensus method is applied to obtain the final clustering results. The proposed voting-XCSc has been evaluated on both the toy examples as well as two real clustering-related applications. i.e, lung cancer image identification, image segmentation. The results demonstrate the voting-XCSc can obtain the superior performance compared with XCSc, K-means, and other state-of-the-arts. © 2013 Springer-Verlag.
    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
    Pages603-610
    Number of pages7
    Volume8206
    DOIs
    Publication statusPublished - 2013
    Event14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013 - Hefei
    Duration: 1 Jul 2013 → …
    http://www.scopus.com/inward/record.url?eid=2-s2.0-84890880494&partnerID=40&md5=975f18dd51454449a25bac48fdeb2cfd

    Conference

    Conference14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013
    CityHefei
    Period1/07/13 → …
    Internet address

    Keywords

    • Consensus Clustering
    • Learning Classifier System
    • Reinforcement Learning

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