Using genetic programming for the induction of oblique decision trees

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@InProceedings{Shali:2007:ICMLA,
  author =       "Amin Shali and Mohammad Reza Kangavari and 
                 Bahareh Bina",
  title =        "Using genetic programming for the induction of oblique
                 decision trees",
  booktitle =    "Sixth International Conference on Machine Learning and
                 Applications, ICMLA 2007",
  year =         "2007",
  month =        dec,
  pages =        "38--43",
  keywords =     "genetic algorithms, genetic programming, genetically
                 induced oblique decision tree algorithm, internal node,
                 oblique decision trees, optimal testing criterion,
                 decision trees",
  URL =          "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4457205",
  DOI =          "doi:10.1109/ICMLA.2007.66",
  abstract =     "In this paper, we present a genetically induced
                 oblique decision tree algorithm. In traditional
                 decision tree, each internal node has a testing
                 criterion involving a single attribute. Oblique
                 decision tree allows testing criterion to consist of
                 more than one attribute. Here we use genetic
                 programming to evolve and find an optimal testing
                 criterion in each internal node for the set of samples
                 at that node. This testing criterion is the
                 characteristic function of a relation over existing
                 attributes. We present the algorithm for construction
                 of the oblique decision tree. We also compare the
                 results of our proposed oblique decision tree with the
                 one of C4.5 algorithm.",
  notes =        "Also known as \cite{4457205}",
}

Genetic Programming entries for Amin Shali Mohammad Reza Kangavari Bahareh Bina

Citations