Demoting redundant features to improve the discriminatory ability in cancer data

Journal of Biomedical Informatics

Volumn 42, Issue 4, 2009, Pages 721-725

  Osl, M ^a   Dreiseitl, S ^a,b   Cerqueira, F ^a   Netzer, M ^a   Pfeifer, B ^a   Baumgartner, C ^a  

^a UNIVERSITY FOR HEALTH SCIENCES   (Austria)

^b UNIVERSITY OF APPLIED SCIENCES UPPER AUSTRIA   (Austria)

Author keywords

Correlation; Data mining; Feature selection; Knowledge discovery; Lung cancer; Melanoma; Redundancy

Indexed keywords

CORRELATION; FEATURE SELECTION; KNOWLEDGE DISCOVERY; LUNG CANCER; MELANOMA;

BIOLOGICAL ORGANS; FEATURE EXTRACTION; INFORMATION MANAGEMENT; MINING; REDUNDANCY; STATISTICAL TESTS;

QUALITY ASSURANCE;

ARTICLE; DATA MINING; INFORMATION PROCESSING; LEARNING ALGORITHM; LUNG CANCER; MEDICAL INFORMATICS; MEDICAL LITERATURE; MELANOMA; PRIORITY JOURNAL;

ALGORITHMS; DATABASES, GENETIC; GENOMICS; HUMANS; LOGISTIC MODELS; MODELS, BIOLOGICAL; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; TUMOR MARKERS, BIOLOGICAL;

EID: 67649306223     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2009.05.006     Document Type: Article

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