Improved Random Forest for Classification
We propose an improved random forest classifier that performs classification with minimum number of trees. The proposed method iteratively removes some unimportant features. Based on the number of important and unimportant features, we formulate a novel theoretical upper limit on the number of trees...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 27(2018), 8 vom: 09. Aug., Seite 4012-4024
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| 1. Verfasser: |
Paul, Angshuman
(VerfasserIn) |
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| Weitere Verfasser: |
Mukherjee, Dipti Prasad,
Das, Prasun,
Gangopadhyay, Abhinandan,
Chintha, Appa Rao,
Kundu, Saurabh |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2018
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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