Prediction of chemical carcinogenicity by machine learning approaches

SAR and QSAR in Environmental Research

Volumn 20, Issue 1-2, 2009, Pages 27-75

  Li, X Y ^a   Tan, N X ^a   Rao, H B ^a   Li, Z R ^a  

^a SICHUAN UNIVERSITY   (China)

Author keywords

Carcinogenicity; Feature selection; Monte Carlo simulated annealing; Support vector machine

Indexed keywords

CLASSIFICATION (OF INFORMATION); FEATURE SELECTION; FORECASTING; MONTE CARLO METHODS; NEURAL NETWORKS; SIMULATED ANNEALING;

CARCINOGENIC COMPOUNDS; CARCINOGENICITY; CHEMICAL CARCINOGENICITY; DESCRIPTORS; FEATURES SELECTION; MODEL CONSTRUCTION; MONTE CARLO SIMULATED ANNEALING; OVERALL ACCURACIES; PREDICTION ACCURACY; SUPPORT VECTORS MACHINE;

SUPPORT VECTOR MACHINES;

CARCINOGEN; INORGANIC COMPOUND; ORGANIC COMPOUND;

ARTICLE; ARTIFICIAL INTELLIGENCE; CHEMISTRY; FORECASTING; METHODOLOGY; STATISTICAL MODEL;

ARTIFICIAL INTELLIGENCE; CARCINOGENS; FORECASTING; INORGANIC CHEMICALS; MODELS, STATISTICAL; ORGANIC CHEMICALS;

EID: 67650878964     PISSN: 1062936X     EISSN: 1029046X     Source Type: Journal    
DOI: 10.1080/10629360902724085     Document Type: Article

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