Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

Soft Computing

Volumn 20, Issue 8, 2016, Pages 2967-2979

  Mistry, Pritesh ^a   Neagu, Daniel ^a   Trundle, Paul R ^a   Vessey, Jonathan D ^b  

^a UNIVERSITY OF BRADFORD   (United Kingdom)

^b LHASA LIMITED   (United Kingdom)

Author keywords

Area under the curve; Big data in toxicology; Classification; Data mining; Decision tree; Random forest; Vehicle toxicity modelling

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIG DATA; CLASSIFICATION (OF INFORMATION); DECISION TREES; FORECASTING; LEARNING ALGORITHMS; LEARNING SYSTEMS; TOXICITY; VEHICLES;

AREA UNDER THE CURVES; CLASSIFICATION MODELS; DECISION TREE MODELS; FUNCTIONAL RELATIONSHIP; MACHINE LEARNING TECHNIQUES; NATIONAL INSTITUTE OF HEALTHS; PREDICTION ACCURACY; RANDOM FORESTS;

DATA MINING;

EID: 84947737338     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-015-1925-9     Document Type: Article

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