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Classifier Design Given an Uncertainty Class of Feature Distributions via Regularized Maximum Likelihood and the Incorporation of Biological Pathway Knowledge in Steady-State Phenotype Classification
Contemporary high-throughput technologies provide measurements of very large numbers of variables but often with very small sample sizes. This paper proposes an optimization-based paradigm for utilizing prior knowledge to design better performing classifiers when sample sizes are limited. We derive...
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| Publicat a: | Pattern Recognit |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2013
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4535735/ https://ncbi.nlm.nih.gov/pubmed/26279589 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.patcog.2013.02.017 |
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