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    DIS
    1999
    Springer
    126views Theoretical Computer Science» more  DIS 1999»
    Approximation of Optimal Two-Dimensional Association Rules for Categorical Attributes Using Semidefinite Programming
    13 years 10 months ago
    Approximation of Optimal Two-Dimensional Association Rules for Categorical Attributes Using Semidefinite Programming
    Download  sdpa.indsys.chuo-u.ac.jp
    Katsuki Fujisawa, Yukinobu Hamuro, Naoki Katoh, Ta...
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    DIS
    1999
    Springer
    88views Theoretical Computer Science» more  DIS 1999»
    Graph-Based Induction for General Graph Structured Data
    13 years 10 months ago
    Graph-Based Induction for General Graph Structured Data
    Download  www.ar.sanken.osaka-u.ac.jp
    Takashi Matsuda, Tadashi Horiuchi, Hiroshi Motoda,...
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    DIS
    1999
    Springer
    76views Theoretical Computer Science» more  DIS 1999»
    Knowledge Discovery from Health Data Using Weighted Aggregation Classifiers
    13 years 10 months ago
    Knowledge Discovery from Health Data Using Weighted Aggregation Classifiers
    Download  www.i.kyushu-u.ac.jp
    Toru Takae, Minoru Chikamune, Hiroki Arimura, Ayum...
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    DIS
    1999
    Springer
    62views Theoretical Computer Science» more  DIS 1999»
    Scheduled Discovery of Exception Rules
    13 years 10 months ago
    Scheduled Discovery of Exception Rules
    Download  eric.univ-lyon2.fr
    This paper shows preliminary results, on financial data, of an algorithm for discovering pairs of an exception rule and a common sense rule under a prespecified schedule. An exce...
    Einoshin Suzuki
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    DIS
    1999
    Springer
    107views Theoretical Computer Science» more  DIS 1999»
    Discovery of a Set of Nominally Conditioned Polynomials
    13 years 10 months ago
    Discovery of a Set of Nominally Conditioned Polynomials
    Download  bonsai.hgc.jp
    : This paper shows that a connectionist law discovery method called RF5X can discover a law in the form of a set of nominally conditioned polynomials, from data containing both nom...
    Ryohei Nakano, Kazumi Saito
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