Descripción
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The "large k (genes), small N (samples)" phenomenon complicates the problem of microarray classification with logistic regression. The indeterminacy of the maximum likelihood solutions, multicollinearity of predictor variables and data over-fitting cause unstable parameter estimates. Moreover, computational problems arise due to the large number of predictor (genes) variables. Regularized logistic regression excels as a solution. However, the difficulties found here involve an objective function hard to be optimized from a mathematical viewpoint and a careful required tuning of the regularization parameters. | |
Internacional
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Si |
JCR del ISI
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Si |
Título de la revista
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METHODS OF INFORMATION IN MEDICINE |
ISSN
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0026-1270 |
Factor de impacto JCR
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1,057 |
Información de impacto
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Volumen
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48 |
DOI
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Número de revista
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3 |
Desde la página
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236 |
Hasta la página
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241 |
Mes
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ENERO |
Ranking
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