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An Efficient, Parallelized Algorithm for Optimal Conditional Entropy-Based Feature Selection
In Machine Learning, feature selection is an important step in classifier design. It consists of finding a subset of features that is optimum for a given cost function. One possibility to solve feature selection is to organize all possible feature subsets into a Boolean lattice and to exploit the fa...
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| Publicado no: | Entropy (Basel) |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7516975/ https://ncbi.nlm.nih.gov/pubmed/33286261 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e22040492 |
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