Incremental learning of new classes in unbalanced datasets: Learn ++.UDNC

Gregory Ditzler, Michael D. Muhlbaier, Robi Polikar

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

    18 Scopus citations

    Abstract

    We have previously described an incremental learning algorithm, Learn ++.NC, for learning from new datasets that may include new concept classes without accessing previously seen data. We now propose an extension, Learn++.UDNC, that allows the algorithm to incrementally learn new concept classes from unbalanced datasets. We describe the algorithm in detail, and provide some experimental results on two separate representative scenarios (on synthetic as well as real world data) along with comparisons to other approaches for incremental and/or unbalanced dataset approaches.

    Original languageEnglish (US)
    Title of host publicationMultiple Classifier Systems - 9th International Workshop, MCS 2010, Proceedings
    Pages33-42
    Number of pages10
    DOIs
    StatePublished - May 14 2010
    Event9th International Workshop on Multiple Classifier Systems, MCS 2010 - Cairo, Egypt
    Duration: Apr 7 2010Apr 9 2010

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume5997 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other9th International Workshop on Multiple Classifier Systems, MCS 2010
    CountryEgypt
    CityCairo
    Period4/7/104/9/10

    All Science Journal Classification (ASJC) codes

    • Theoretical Computer Science
    • Computer Science(all)

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