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Sparse Contribution Feature Selection and Classifiers Optimized by Concave-Convex Variation for HCC Image Recognition
Accurate classification of hepatocellular carcinoma (HCC) image is of great importance in pathology diagnosis and treatment. This paper proposes a concave-convex variation (CCV) method to optimize three classifiers (random forest, support vector machine, and extreme learning machine) for the more ac...
Uloženo v:
| Vydáno v: | Biomed Res Int |
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| Hlavní autoři: | , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Hindawi
2017
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5535756/ https://ncbi.nlm.nih.gov/pubmed/28798937 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/9718386 |
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