In silico prediction of toxic action mechanisms of phenols for imbalanced data with random forest learner

Journal of Molecular Graphics and Modelling

Volumn 35, Issue , 2012, Pages 21-27

  Chen, Jing ^a   Tang, Yuan Yan ^a,b   Fang, Bin ^a   Guo, Chang ^a  

^a CHONGQING UNIVERSITY   (China)

^b UNIVERSITY OF MACAU   (Macao)

Author keywords

Cost sensitive; Phenols; QSAR; Random Forest; Toxic action mechanisms

Indexed keywords

COMPUTATIONAL EXPERIMENT; COST MATRICES; COST-SENSITIVE; COST-SENSITIVE LEARNING; DATA CLASS; DATA IMBALANCE; DATA SETS; ENVIRONMENTAL HAZARDS; EXPLORATION TECHNIQUES; IMBALANCED DATA; IN-SILICO; LOCAL MODEL; MACHINE LEARNING TECHNIQUES; MISCLASSIFICATIONS; MOLECULAR DESCRIPTORS; PRACTICAL PROBLEMS; PREDICTION ACCURACY; PREDICTION MODEL; PREDICTION PERFORMANCE; QSAR; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP; RANDOM FORESTS; RARE CLASS; SAFETY ASSESSMENTS; TECHNICAL CHALLENGES; TETRAHYMENA PYRIFORMIS; TOXIC ACTION; TOXICITY DATA;

COMPUTATIONAL CHEMISTRY; COSTS; DECISION TREES; FORESTRY; LEARNING SYSTEMS; MATHEMATICAL MODELS; PHENOLS; TOXICITY;

FORECASTING;

PHENOL;

ARTICLE; COMPUTATIONAL FLUID DYNAMICS; COMPUTER MODEL; CONCEPTUAL FRAMEWORK; DATA ANALYSIS; MACHINE LEARNING; MOLECULAR BIOLOGY; MOLECULAR MECHANICS; PREDICTION; PRIORITY JOURNAL; RANDOM FOREST LEARNER; STRUCTURE ACTIVITY RELATION; TETRAHYMENA PYRIFORMIS;

ALGORITHMS; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DECISION TREES; ENVIRONMENTAL POLLUTANTS; MODELS, CHEMICAL; PHENOLS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; ROC CURVE;

COSTS; FORECASTS; FORESTS; MATHEMATICAL MODELS; PHENOLS; TOXICITY;

TETRAHYMENA PYRIFORMIS;

EID: 84859802343     PISSN: 10933263     EISSN: 18734243     Source Type: Journal    
DOI: 10.1016/j.jmgm.2012.01.002     Document Type: Article

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