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Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease
Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily depen...
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| Veröffentlicht in: | Sci Rep |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Nature Publishing Group
2017
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5264393/ https://ncbi.nlm.nih.gov/pubmed/28120883 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/srep41069 |
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