Feature selection to increase the random forest method performance on high dimensional data
Random Forest is a supervised classification method based on bagging (Bootstrap aggregating) Breiman and random selection of features. The choice of features randomly assigned to the Random Forest makes it possible that the selected feature is not necessarily informative. So it is necessary to selec...
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Main Authors: | Prasetiyowati, Maria Irmina (Author), Maulidevi, Nur Ulfa (Author), Surendro, Kridanto (Author) |
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Format: | EJournal Article |
Published: |
Universitas Ahmad Dahlan,
2020-11-06.
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Online Access: | Get Fulltext |
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