Gene selection and cancer microarray data classification via mixed-integer optimization

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4973 LNCS, Issue , 2008, Pages 141-152

  Orsenigo, Carlotta ^a  

^a UNIVERSITY OF MILAN   (Italy)

Author keywords

Discrete support vector machines; Gene selection; Microarray data classification; Mixed integer optimization

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; BIOACTIVITY; BIOCOMMUNICATIONS; BIOINFORMATICS; CLASSIFICATION (OF INFORMATION); DATA MINING; DECISION SUPPORT SYSTEMS; DIAGNOSIS; EDUCATION; GENE EXPRESSION; GENES; INFORMATION MANAGEMENT; INFORMATION SCIENCE; INTEGER PROGRAMMING; KNOWLEDGE MANAGEMENT; MINING; OPTIMIZATION; ROBOT LEARNING; SEARCH ENGINES; TUMORS;

BENCHMARK DATASETS; BIOLOGICAL MEASUREMENTS; CANCER MARKER GENES; CLASSIFICATION ACCURACIES; CLASSIFICATION RULES; COMPUTATIONAL EXPERIMENTS; DATA SETS; EARLY CANCER; EUROPEAN; EVOLUTIONARY COMPUTATION (EC); EXPRESSION LEVELS; GENE EXPRESSION (MICROARRAY) DATA; GENE SELECTION; HEIDELBERG (CO); MACHINE LEARNING METHODS; MACHINE-LEARNING; MICROARRAY DATA CLASSIFICATION; MIXED-INTEGER OPTIMIZATION; MOLECULAR LEVELS; SECOND PHASE; TUMOR DIFFERENTIATION; TWO PHASE ALGORITHMS;

LEARNING SYSTEMS;

EID: 47249090942     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-78757-0_13     Document Type: Conference Paper

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