Feb. 12, 2024, 5:42 a.m. | Keito Tajima Naoki Ichijo Yuta Nakahara Toshiyasu Matsushima

cs.LG updates on arXiv.org arxiv.org

Predictions using a combination of decision trees are known to be effective in machine learning. Typical ideas for constructing a combination of decision trees for prediction are bagging and boosting. Bagging independently constructs decision trees without evaluating their combination performance and averages them afterward. Boosting constructs decision trees sequentially, only evaluating a combination performance of a new decision tree and the fixed past decision trees at each step. Therefore, neither method directly constructs nor evaluates a combination of decision trees …

boosting combination construction cs.lg decision decision trees framework ideas machine machine learning multiple performance prediction predictions process them trees

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