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Guilt-By-Association Feature Selection Applied to Simulated Proteomic Data
We propose a new feature selection algorithm, Guilt-By-Association (GBA), which uses hierarchical clustering based on feature correlations to eliminate redundant features. GBA can be used in conjunction with other algorithms to produce a feature selection routine that explicitly considers both the s...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
American Medical Informatics Association
2005
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC1560499/ https://ncbi.nlm.nih.gov/pubmed/16779401 |
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