Model Discovery and Validation for the Qsar Problem using Association Rule Mining

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Luminita Dumitriu and Cristina Segal and 
                 Marian Craciun and Adina Cocu and Lucian P. Georgescu",
  title =        "Model Discovery and Validation for the Qsar Problem
                 using Association Rule Mining",
  journal =      "International Science Index",
  volume =       "1",
  number =       "11",
  year =         "2007",
  pages =        "648--652",
  keywords =     "genetic algorithms, genetic programming, association
                 rules, classification, data mining, quantitative
                 structure - activity relationship.",
  bibsource =    "",
  publisher =    "World Academy of Science, Engineering and Technology",
  ISSN =         "1307-6892",
  oai =          "oai:CiteSeerX.psu:",
  URL =          "",
  URL =          "",
  URL =          "",
  URL =          "",
  size =         "5 pages",
  abstract =     "There are several approaches in trying to solve the
                 Quantitative Structure-Activity Relationship (QSAR)
                 problem. These approaches are based either on
                 statistical methods or on predictive data mining. Among
                 the statistical methods, one should consider regression
                 analysis, pattern recognition (such as cluster
                 analysis, factor analysis and principal components
                 analysis) or partial least squares. Predictive data
                 mining techniques use either neural networks, or
                 genetic programming, or neuro-fuzzy knowledge. These
                 approaches have a low explanatory capability or non at
                 all. This paper attempts to establish a new approach in
                 solving QSAR problems using descriptive data mining.
                 This way, the relationship between the chemical
                 properties and the activity of a substance would be
                 comprehensibly modelled.",
  notes =        "International Science Index 11, 2007",

Genetic Programming entries for Luminita Dumitriu Cristina Segal Marian Craciun Adina Cocu Lucian P Georgescu