Using Gaussian distribution to construct fitness functions in genetic programming for multiclass object classification

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@Article{zhang:2006:PRL,
  author =       "Mengjie Zhang and Will Smart",
  title =        "Using Gaussian distribution to construct fitness
                 functions in genetic programming for multiclass object
                 classification",
  journal =      "Pattern Recognition Letters",
  year =         "2006",
  volume =       "27",
  number =       "11",
  pages =        "1266--1274",
  month =        aug,
  note =         "Evolutionary Computer Vision and Image Understanding",
  keywords =     "genetic algorithms, genetic programming, Probability
                 based genetic programming, Object recognition, Object
                 detection, Fitness function, Multiclass
                 classification",
  DOI =          "doi:10.1016/j.patrec.2005.07.024",
  abstract =     "the use of Gaussian distribution in genetic
                 programming (GP) for multiclass object classification
                 problems. Instead of using predefined multiple
                 thresholds to form different regions in the program
                 output space for different classes, this approach uses
                 probabilities of different classes, derived from
                 Gaussian distributions, to construct the fitness
                 function for classification. Two fitness measures,
                 overlap area and weighted distribution distance, have
                 been developed. Rather than using the best evolved
                 program in a population, this approach uses multiple
                 programs and a voting strategy to perform
                 classification. The approach is examined on three multi
                 class object classification problems of increasing
                 difficulty and compared with a basic GP approach. The
                 results suggest that the new approach is more effective
                 and more efficient than the basic GP approach. Although
                 developed for object classification, this approach is
                 expected to be able to be applied to other
                 classification problems.",
  notes =        "Special Issue on Evolutionary Computer Vision and
                 Image Understanding, Pattern Recognition Letters, An
                 official publication of the International Association
                 for Pattern Recognition",
}

Genetic Programming entries for Mengjie Zhang Will Smart

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