Removing redundant features via clustering: preliminary results in mental task separation

Renato Cordeiro De Amorim, Boris Mirkin

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    Abstract

    Recent clustering algorithms have been designed to take into account the degree of relevance of each feature, by automatically calculating their weights. However, as the tendency is to evaluate each feature at a time, these algorithms may have difficulties dealing with features containing similar information. Should this information be relevant, these algorithms would set high weights to all such features instead of removing some due to their redundant nature.
    In this paper we introduce an unsupervised feature selection method that targets redundant features. Our method clusters similar features together and selects a subset of representative features for each cluster. This selection is based on the maximum information compression index between each feature and its respective cluster centroid. We empirically validate out method by comparing with it with a popular unsupervised feature selection on three EEG data sets. We find that ours selects features that produce better cluster recovery, without the need for an extra user-defined parameter
    Original languageEnglish
    Title of host publicationLooking into the Future of Creativity and Decision Support Systems
    Subtitle of host publicationProceedings of the 8th International Conference on Knowledge, Information and Creativity Support Systems
    EditorsAndrzej M.J. Skulimowski
    PublisherProgress & Business Publishers
    Pages63-72
    ISBN (Electronic)978-83-912831-8-9
    ISBN (Print)978-83-912831-6-5
    Publication statusPublished - 2013
    EventThe 8th International Conference on Knowledge, Information and Creativity Support Systems - Krakow, Poland
    Duration: 7 Nov 20139 Nov 2013

    Conference

    ConferenceThe 8th International Conference on Knowledge, Information and Creativity Support Systems
    Country/TerritoryPoland
    CityKrakow
    Period7/11/139/11/13

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