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Utility metric for unsupervised feature selection
Feature selection techniques are very useful approaches for dimensionality reduction in data analysis. They provide interpretable results by reducing the dimensions of the data to a subset of the original set of features. When the data lack annotations, unsupervised feature selectors are required fo...
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| Veröffentlicht in: | PeerJ Comput Sci |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
PeerJ Inc.
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8080425/ https://ncbi.nlm.nih.gov/pubmed/33981839 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.477 |
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