Understanding the prediction of transmembrane proteins by support vector machine using association rule mining

2007 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, CIBCB 2007

Volumn , Issue , 2007, Pages 418-425

  Hu, Hae Jin ^a   Wang, Hao ^c   Harrison, Robert ^b   Tai, Phang C ^b   Pan, Yi ^b  

^a Molecular Basis of Disease Program   (United States)

^b GEORGIA STATE UNIVERSITY   (United States)

^c NONE

Author keywords

Association rule based classifier; CPAR; Decision tree; PCPAR; Support vector machine

Indexed keywords

BETTER PERFORMANCE; COMPUTATIONAL APPROACH; CPAR; PCPAR; PROTEIN STRUCTURES; RULE-BASED CLASSIFIER; TRANS-MEMBRANE PROTEINS; UNDERSTANDABILITY;

ARTIFICIAL INTELLIGENCE; ASSOCIATION RULES; BIOINFORMATICS; DATA MINING; DECISION TREES; PROTEINS;

SUPPORT VECTOR MACHINES;

EID: 38049078106     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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