K-means clustering based filter feature selection on high dimensional data
With hundreds or thousands of features in high dimensional data, computational workload is challenging. In classification process, features which do not contribute significantly to prediction of classes, add to the computational workload. Therefore the aim of this paper is to use feature selection t...
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| Hoofdauteurs: | , , |
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| Formaat: | EJournal Article |
| Gepubliceerd in: |
Universitas Ahmad Dahlan,
2016-03-31.
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| Online toegang: | Get Fulltext |
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| Plaatsingsnummer: |
A1234.567 |
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| Kopie 1 | Beschikbaar |