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An Adaptive Weighted Deep Forest Classifier | | Lev V. Utkin
; Andrei V. Konstantinov
; Viacheslav S. Chukanov
; Mikhail V. Kots
; Anna A. Meldo
; | | Date: |
Fri, 4 Jan 2019 22:45:22 GMT (1895kb,D) | | Abstract: | A modification of the confidence screening mechanism based on adaptive
weighing of every training instance at each cascade level of the Deep Forest is
proposed. The idea underlying the modification is very simple and stems from
the confidence screening mechanism idea proposed by Pang et al. to simplify the
Deep Forest classifier by means of updating the training set at each level in
accordance with the classification accuracy of every training instance.
However, if the confidence screening mechanism just removes instances from
training and testing processes, then the proposed modification is more flexible
and assigns weights by taking into account the classification accuracy. The
modification is similar to the AdaBoost to some extent. Numerical experiments
illustrate good performance of the proposed modification in comparison with the
original Deep Forest proposed by Zhou and Feng. | | Source: | arXiv, 1901.1334 | | Services: | Forum | Review | PDF | Favorites | |
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