Feature selection for co-training: A QSAR study

Proceedings of the 2007 International Conference on Artificial Intelligence, ICAI 2007

Volumn 1, Issue , 2007, Pages 138-144

  Li, Guo Zheng ^a,b   Li, Dan ^a   Lu, Wen Cong ^a   Yang, Mary Q ^c   Yang, Jack Y ^d  

^a SHANGHAI UNIVERSITY   (China)

^b NANJING UNIVERSITY   (China)

^c NATIONAL HUMAN GENOME RESEARCH INSTITUTE   (United States)

^d HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CO-TRAINING; DATA SETS; DRUG MOLECULES; EXPERIMENTAL METHODS; FEATURE SELECTION METHODS; HIGH COSTS; LONG CYCLES; MOLECULAR ACTIVITIES; NOVEL ALGORITHM; NUMERICAL EXPERIMENTAL; PREDICTION ACCURACY; QSAR MODEL; QSAR STUDIES; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP; SEMI-SUPERVISED LEARNING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL CHEMISTRY; MOLECULAR GRAPHICS; MOLECULES; SUPERVISED LEARNING;

FORECASTING;

EID: 84866524595     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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