Learning First-order Relations from Noisy Databases using Genetic Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Man Leung Wong and Kwong Sak Leung",
  title =        "Learning First-order Relations from Noisy Databases
                 using Genetic Algorithms",
  booktitle =    "Proceedings of the Second Singapore International
                 Conference on Intelligent Systems",
  year =         "1994",
  pages =        "B159--164",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://cptra.ln.edu.hk/~mlwong/conference/spicis1994.pdf",
  abstract =     "In knowledge discovery from databases, we emphasise
                 the need for learning from huge, incomplete and
                 imperfect data sets (Piatetsky-Shapiro and Frawley,
                 1991). To handle noise in the problem domain, existing
                 learning systems avoid overfitting the imperfect
                 training examples by excluding insignificant patterns.
                 The problem is that these systems use a limiting
                 attribute-value language for representing the training
                 examples and induced knowledge. Moreover, some
                 important patterns are ignored because they are
                 statistically insignificant. This paper describes a
                 system called GLPS that combines Genetic Algorithms and
                 a variation of FOIL (Quinlan, 1990) to learn
                 first-order concepts from noisy training examples. The
                 performance of GLPS is evaluated on the chess endgame
                 domain. A detail comparison to FOIL is accomplished and
                 the performance of GLPS is significantly better than
                 that of FOIL. This result indicates that the Darwinian
                 principle of natural selection is a plausible noise
                 handling method which can avoid overfitting and
                 identify important patterns at the same time.",
  notes =        "SPICIS-94",

Genetic Programming entries for Man Leung Wong Kwong-Sak Leung