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Abstract
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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. | |
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International
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Si |
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JCR
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Si |
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Title
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METHODS OF INFORMATION IN MEDICINE |
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ISBN
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0026-1270 |
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Impact factor JCR
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1,057 |
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Impact info
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Volume
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48 |
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Journal number
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3 |
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From page
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236 |
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To page
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241 |
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Month
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ENERO |
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Ranking
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