An efficient algorithm coupled with synthetic minority over-sampling technique to classify imbalanced PubChem BioAssay data

Analytica Chimica Acta

Volumn 806, Issue , 2014, Pages 117-127

  Hao, Ming ^a   Wang, Yanli ^a   Bryant, Stephen H ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

High throughput screening; Imbalanced classification; Over sampling; PubChem; Under sampling

Indexed keywords

HIGH-THROUGHPUT SCREENING; IMBALANCED CLASSIFICATION; OVER SAMPLING; PUBCHEM; UNDER-SAMPLING;

ALGORITHMS; DECISION TREES;

BIOASSAY;

ACCURACY; ARTICLE; CHEMICAL DATABASE; CLASSIFICATION ALGORITHM; COMPUTER PREDICTION; DATA PROCESSING; GLMBOOST ALGORITHM; HIGH THROUGHPUT SCREENING; PRIORITY JOURNAL; RANDOM FOREST; SENSITIVITY AND SPECIFICITY; SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE ALGORITHM;

HIGH-THROUGHPUT SCREENING; IMBALANCED CLASSIFICATION; OVER-SAMPLING; PUBCHEM; UNDER-SAMPLING;

ALGORITHMS; BIOLOGICAL ASSAY; DATABASES, CHEMICAL; HIGH-THROUGHPUT SCREENING ASSAYS;

EID: 84890130251     PISSN: 00032670     EISSN: 18734324     Source Type: Journal    
DOI: 10.1016/j.aca.2013.10.050     Document Type: Article

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