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Feature selection by optimizing a lower bound of conditional mutual information
A unified framework is proposed to select features by optimizing computationally feasible approximations of high-dimensional conditional mutual information (CMI) between features and their associated class label under different assumptions. Under this unified framework, state-of-the-art information...
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| Publicado no: | Inf Sci (Ny) |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6167022/ https://ncbi.nlm.nih.gov/pubmed/30283157 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ins.2017.08.036 |
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