A Niched Genetic Programming Algorithm for Classification Rules Discovery in Geographic Databases

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  title =        "A Niched Genetic Programming Algorithm for
                 Classification Rules Discovery in Geographic
  author =       "Marconi {de Arruda Pereira} and 
                 Clodoveu Augusto {Davis Junior} and Joao Antonio {de Vasconcelos}",
  booktitle =    "Simulated Evolution and Learning - 8th International
                 Conference, {SEAL} 2010, Kanpur, India, December 1-4,
                 2010. Proceedings",
  publisher =    "Springer",
  year =         "2010",
  volume =       "6457",
  editor =       "Kalyanmoy Deb and Arnab Bhattacharya and 
                 Nirupam Chakraborti and Partha Chakroborty and Swagatam Das and 
                 Joydeep Dutta and Santosh K. Gupta and Ashu Jain and 
                 Varun Aggarwal and J{\"u}rgen Branke and 
                 Sushil J. Louis and Kay Chen Tan",
  isbn13 =       "978-3-642-17297-7",
  pages =        "260--269",
  series =       "Lecture Notes in Computer Science",
  URL =          "http://dx.doi.org/10.1007/978-3-642-17298-4",
  DOI =          "doi:10.1007/978-3-642-17298-4_27",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "This paper presents a niched genetic programming tool,
                 called DMGeo, which uses elitism and another techniques
                 designed to efficiently perform classification rule
                 mining in geographic databases. The main contribution
                 of this algorithm is to present a way to work with
                 geographical and conventional data in data mining
                 tasks. In our approach, each individual in the genetic
                 programming represents a classification rule using a
                 Boolean predicate. The adequacy of the individual to
                 the problem is assessed using a fitness function, which
                 determines its chances for selection. In each
                 individual, the predicate combines conventional
                 attributes (Boolean, numeric) and geographic
                 characteristics, evaluated using geometric and
                 topological functions. Our prototype implementation of
                 the tool was compared favourably to other classical
                 classification ones. We show that the proposed niched
                 genetic programming algorithm works efficiently with
                 databases that contain geographic objects, opening up
                 new possibilities for the use of genetic programming in
                 geographic data mining problems.",
  bibdate =      "2010-12-01",
  bibsource =    "DBLP,

Genetic Programming entries for Marconi de Arruda Pereira Clodoveu Augusto Davis Junior Joao Antonio de Vasconcelos