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Adaptive feature selection using v-shaped binary particle swarm optimization
Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate th...
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| I publikationen: | PLoS One |
|---|---|
| Huvudupphovsmän: | , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
Public Library of Science
2017
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5373580/ https://ncbi.nlm.nih.gov/pubmed/28358850 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0173907 |
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