Transductive support vector machines: Promising approach to model small and unbalanced datasets

Molecular Informatics

Volumn 32, Issue 3, 2013, Pages 261-266

  Kondratovich, Evgeny ^a,b   Baskin, Igor I ^b   Varnek, Alexandre ^a  

^a UNIVERSITÉ LOUIS PASTEUR   (France)

^b MOSCOW STATE UNIVERSITY   (Russian Federation)

Author keywords

DUD; QSAR; Semi supervised learning; TSVM

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL CHEMISTRY;

CHEMOINFORMATICS; DUD; LABELED AND UNLABELED DATA; MACHINE-LEARNING; QSAR; SEMI-SUPERVISED LEARNING; SEMI-SUPERVISED METHOD; SMALL DATA SET; TRANSDUCTIVE SUPPORT VECTOR MACHINE; UNBALANCED DATASETS;

SUPPORT VECTOR MACHINES;

ACETYLCHOLINESTERASE; ANDROGEN RECEPTOR; CYCLOOXYGENASE 1; DIPEPTIDYL CARBOXYPEPTIDASE; GLUCOCORTICOID RECEPTOR; HEAT SHOCK PROTEIN; HUMAN IMMUNODEFICIENCY VIRUS PROTEINASE; PHOSPHODIESTERASE; RNA DIRECTED DNA POLYMERASE; THROMBIN;

ARTICLE; BIOLOGICAL ACTIVITY; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SUPPORT VECTOR MACHINE; TRANSDUCTIVE SUPPORT VECTOR MACHINE;

EID: 84875345531     PISSN: 18681743     EISSN: 18681751     Source Type: Journal    
DOI: 10.1002/minf.201200135     Document Type: Article

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