ANVAS: artificial neural variables adaptation system for descriptor selection.
A new algorithm model-oriented for variable selection is presented in this study. It is based on the combination of genetic algorithms (GA) for hyperspace exploration, and counterpropagation artificial neural network (CP ANN) for deriving the fitness score. The proposed method performed very well on both well defined synthetic data sets and real academic data sets.
Mazzatorta
Paolo
P
Istituto Mario Negri, via Eritrea 62, 20157 Milan, Italy. mazzatorta@marionegri.it
Vracko
Marjan
M
Benfenati
Emilio
E
D000465:Algorithms; D002273:Carcinogens / Q000737:chemistry / Q000494:pharmacology; D002875:Chromosomes / Q000235:genetics; D003198:Computer Simulation; D019143:Evolution, Molecular; D005838:Genotype; D008957:Models, Genetic; D009153:Mutagens / Q000737:chemistry / Q000494:pharmacology; D009154:Mutation / Q000187:drug effects / Q000235:genetics; D016571:Neural Networks, Computer; D010641:Phenotype; D025341:Principal Component Analysis; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D012641:Selection, Genetic
D002273:Carcinogens; D009153:Mutagens