A self-adaptive genetic algorithm-artificial neural network algorithm with leave-one-out cross validation for descriptor selection in QSAR study

Journal of Computational Chemistry

Volumn 31, Issue 10, 2010, Pages 1956-1968

  Wu, Jingheng ^a   Mei, Juan ^a   Wen, Sixiang ^a   Liao, Siyan ^a   Chen, Jincan ^a   Shen, Y ^a  

^a SUN YAT SEN UNIVERSITY   (China)

Author keywords

Artificial neural network; Genetic algorithms; Leave multiple out; Leave one out; Multiple linear regression; Quantitative structure activity relationship; Y randomization

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK ALGORITHM; ARTIFICIAL NEURAL NETWORKS; BIOLOGICAL ACTIVITIES; CROSS VALIDATION; CROSS-VALIDATION TECHNIQUE; DESCRIPTORS; LEAVE-ONE-OUT; MULTIPLE LINEAR REGRESSIONS; OVERFITTING; PREDICTIVE POWER; QSAR MODEL; QSAR STUDIES; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS; ROOT MEAN SQUARE DEVIATIONS; SELF ADAPTIVE GENETIC ALGORITHM; SELF-ADAPTIVE; STEPWISE MULTIPLE LINEAR REGRESSION; TRAINING ALGORITHMS;

ADAPTIVE ALGORITHMS; BACKPROPAGATION ALGORITHMS; DYES; GENETIC ALGORITHMS; LINEAR REGRESSION; MOLECULAR GRAPHICS; ORGANIC CHEMICALS; TOXIC MATERIALS;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICAL MODEL;

ALGORITHMS; LINEAR MODELS; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 77953405089     PISSN: 01928651     EISSN: 1096987X     Source Type: Journal    
DOI: 10.1002/jcc.21471     Document Type: Article

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