Computational Hybrids Towards Software Defect Predictions

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

@Article{Banga:2013:ijset,
  author =       "Manu Banga",
  title =        "Computational Hybrids Towards Software Defect
                 Predictions",
  journal =      "International Journal of Scientific Engineering and
                 Technology",
  year =         "2013",
  volume =       "2",
  number =       "5",
  pages =        "311--316",
  ISSN =         "2277-1581",
  bibsource =    "OAI-PMH server at doaj.org",
  language =     "English",
  oai =          "oai:doaj.org/article:12a6cd2f16e947d7969f01df7e2544d9",
  rights =       "CC by-nc-nd",
  keywords =     "genetic algorithms, genetic programming, MLR, SVR,
                 CART, MARS, MPFF, RBF",
  URL =          "http://ijset.com/ijset/publication/v2s5/paper1.pdf",
  abstract =     "In this paper, new computational intelligence
                 sequential hybrid architectures involving Genetic
                 Programming (GP) and Group Method of Data Handling
                 (GMDH) viz. GPGMDH. Three linear ensembles based on (i)
                 arithmetic mean (ii) geometric mean and (iii) harmonic
                 mean are also developed. We also performed GP based
                 feature selection. The efficacy of Multiple Linear
                 Regression (MLR), Polynomial Regression, Support Vector
                 Regression (SVR), Classification and Regression Tree
                 (CART), Multivariate Adaptive Regression Splines
                 (MARS), Multilayer FeedForward Neural Network (MLFF),
                 Radial Basis Function Neural Network (RBF), Counter
                 Propagation Neural Network (CPNN), Dynamic Evolving
                 Neuro--Fuzzy Inference System (DENFIS), TreeNet, Group
                 Method of Data Handling and Genetic Programming is
                 tested on the NASA dataset. Ten-fold cross validation
                 and t-test are performed to see if the performances of
                 the hybrids developed are statistically significant.",
}

Genetic Programming entries for Manu Banga

Citations