Oblique Decision Tree Ensemble via Twin Bounded SVM

Volume: 143, Pages: 113072 - 113072
Published: Apr 1, 2020
Abstract
Ensemble methods with “perturb and combine” strategy have shown improved performance in the classification problems. Recently, random forest algorithm was ranked one among 179 classifiers evaluated on 121 UCI datasets. Motivated by this, we propose a new approach for the generation of oblique decision trees. At each non-leaf node, the training data samples are grouped in two categories based on the Bhattachrayya distance with randomly selected...
Paper Details
Title
Oblique Decision Tree Ensemble via Twin Bounded SVM
Published Date
Apr 1, 2020
Volume
143
Pages
113072 - 113072
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