Intelligent Combination of Kernels Information for Improved Classification

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Abdul Majid and Asifullah Khan and Anwar M. Mirza",
  title =        "Intelligent Combination of Kernels Information for
                 Improved Classification",
  booktitle =    "Fourth International Conference on Machine Learning
                 and Applications (ICMLA'05)",
  year =         "2005",
  pages =        "16--21",
  address =      "Los Angeles",
  publisher_address = "Los Alamitos, CA, USA",
  publisher =    "IEEE Computer Society",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7695-2495-8",
  DOI =          "doi:10.1109/ICMLA.2005.42",
  abstract =     "we are proposing a combination scheme of kernels
                 information of Support Vector Machines (SVMs) for
                 improved classification task using Genetic Programming.
                 In the scheme, first, the predicted information is
                 extracted by SVM through the learning of different
                 kernel functions. GP is then used to develop an Optimal
                 Composite Classifier (OCC) having better performance
                 than individual SVM classifiers. The experimental
                 results demonstrate that OCC is more effective,
                 generalised and robust. Specifically, it attains high
                 margin of improvement at small features. Another side
                 advantage of our GP based intelligent combination
                 scheme is that it automatically incorporates the issues
                 of optimal kernel and model selection to achieve a
                 higher performance prediction model.",
  notes =        "",

Genetic Programming entries for Abdul Majid Asifullah Khan Anwar M Mirza