Genetic Programming in Data Mining - Cellular Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@MastersThesis{takac:masters,
  author =       "Aleksandra Takac",
  title =        "Genetic Programming in Data Mining - Cellular
                 Approach",
  school =       "Institute of Informatics Faculty of Mathematics,
                 Physics and Informatics, Comenius University",
  year =         "2003",
  address =      "Bratislava, Slovakia",
  month =        apr,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.ii.fmph.uniba.sk/~takaca/thesis/thesis.pdf",
  size =         "70 pages",
  notes =        "First results will be here soon of cellular genetic
                 programming on classification task on 3 different
                 datasets (from the link above): German Credit,
                 Australian Credit and Heart disease. Here is another
                 very good link with dataset links : Datasets for Data
                 Mining Also I recommend this very good website for
                 datamining and knowledge discovery:
                 http://www.kdnuggets.com/

                 The test I perform uses sql queries for evaluating
                 individuals of population, genetic programing model is
                 cellular, 2 types of attributes are considered
                 continuous and qualitative. In all examples are 2
                 classes, the results can be compared to other
                 algorithms that were in the project STATLOG. Method for
                 testing the algorithm is 10 and 9-Fold Cross
                 Validation.

                 (01/04/2003)

                 The experiment and results of classification task with
                 cellular genetic programming.

                 (05/04/2003)

                 Third chapter - Data Mining",
}

Genetic Programming entries for Aleksandra Takac

Citations