Selection of fitness function in genetic programming for binary classification

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Muhammad Waqar Aslam",
  booktitle =    "Science and Information Conference (SAI 2015)",
  title =        "Selection of fitness function in genetic programming
                 for binary classification",
  year =         "2015",
  pages =        "489--493",
  abstract =     "Fitness function is a key parameter in genetic
                 programming (GP) and is also known as the driving force
                 of GP. It determines how well a solution is able to
                 solve the given problem. The design of fitness function
                 is instrumental in performance improvement of GP. In
                 this study we evaluate different fitness functions for
                 binary classification using two benchmarking datasets.
                 Two types of fitness functions are used. One type uses
                 statistical distribution of classes in the datasets and
                 the other uses machine learning classifiers. A detailed
                 analysis and comparison are given between different
                 fitness functions in terms of performance and
                 computational complexity.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/SAI.2015.7237187",
  month =        jul,
  notes =        "Also known as \cite{7237187}",

Genetic Programming entries for Muhammad Waqar Aslam