A balanced iterative random forest for gene selection from microarray data

BMC Bioinformatics

Volumn 14, Issue 1, 2013, Pages

  Anaissi, Ali ^a   Kennedy, Paul J ^a   Goyal, Madhu ^a   Catchpoole, Daniel R ^b  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

^b CHILDREN S HOSPITAL AT WESTMEAD   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

GENE EXPRESSION MICROARRAY; HIGH DIMENSIONAL DATASETS; IMBALANCED CLASS; IMBALANCED DATA-SETS; INFORMATIVE GENES; MICROARRAY DATA SETS; MICROARRAY TECHNOLOGIES; STATE-OF-THE-ART METHODS;

ALGORITHMS; DECISION TREES; DISEASES; EXPERIMENTS; GENE EXPRESSION; SUPPORT VECTOR MACHINES;

ITERATIVE METHODS;

ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; CHILD; DNA MICROARRAY; FEMALE; GENE EXPRESSION PROFILING; GENETIC MARKER; GENETICS; HUMAN; METABOLISM; METHODOLOGY; NEOPLASM; REPRODUCIBILITY; SUPPORT VECTOR MACHINE;

BAYES THEOREM; CHILD; COMPUTATIONAL BIOLOGY; FEMALE; GENE EXPRESSION PROFILING; GENETIC MARKERS; HUMANS; MODELS, GENETIC; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; SUPPORT VECTOR MACHINES;

EID: 84883640831     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-14-261     Document Type: Article

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