Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Guo, Yu ^a   Graber, Armin ^b   McBurney, Robert N ^c   Balasubramanian, Raji ^d  

^a BG Medicine Inc   (United States)

^b UNIVERSITY FOR HEALTH SCIENCES   (Austria)

^c Optimal Medicine Ltd   (United Kingdom)

^d UNIVERSITY OF MASSACHUSETTS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

'OMICS' TECHNOLOGIES; BIOLOGICAL VARIATION; CLASS DISTRIBUTIONS; CLASSIFICATION ALGORITHM; FEATURE DISTRIBUTION; K-NEAREST NEIGHBORS; SIMULATION STRATEGIES; STATISTICAL SOFTWARE;

ALGORITHMS; DATA PROCESSING; DECISION TREES; DESIGN; FORECASTING; MASS SPECTROMETRY; OPTIMIZATION;

COMPUTER SOFTWARE;

ANIMALIA;

ALGORITHM; ANIMAL; ARTICLE; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; COMPARATIVE STUDY; DNA MICROARRAY; FACTUAL DATABASE; GENE EXPRESSION PROFILING; HUMAN; METHODOLOGY; SAMPLE SIZE; STATISTICAL MODEL;

ALGORITHMS; ANIMALS; CLASSIFICATION; DATABASES, FACTUAL; GENE EXPRESSION PROFILING; HUMANS; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; SAMPLE SIZE;

EID: 77956468993     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-447     Document Type: Article

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