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Centralna tehniška knjižnica Univerze v Ljubljani (CTK)
  • Machine-learning with cellular automata
    Povalej, Petra ...
    As the possibility of combining different classifiers into Multiple Classifier System (MCS) becomes an important direction in machine-learning, difficulties arise in choosing the appropriate ... classifiers to combine and choosing the way for combining their decisions. Therefore in this paper we present a novel approach - Classificational Cellular Automata (CCA). The basic idea of CCA is to combine different classifiers induced on the basis of various machine-learning methods into MCS in a non-predefined way. After several iterations of applying adequate transaction rules only a set of the most appropriate classifiers for solving a specific problem is preserved. We empirically showed that the superior results compared to AdaBoost ID3 are a direct consequence of self-organization abilities of CCA. The presented results also pointed out important advantages of CCA, such as: problem independency, robustness to noise and no need for user input.
    Vir: Advances in intelligent data analysis VI : 6th international symposium on intelligent data analysis, IDA 2005, Madrid, Spain, September 8-10, 2005 : proceedings (Str. 305-315)
    Vrsta gradiva - prispevek na konferenci
    Leto - 2005
    Jezik - angleški
    COBISS.SI-ID - 9878806

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