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Feb, 2024
基于Boosting的顺序元树集成构建优化决策树
Boosting-Based Sequential Meta-Tree Ensemble Construction for Improved Decision Trees
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Ryota Maniwa, Naoki Ichijo, Yuta Nakahara, Toshiyasu Matsushima
TL;DR
使用增强学习方法构建多个元树以提高预测性能,防止过度深化的树引起过拟合的问题,并通过实验与单个决策树的集合进行性能比较。
Abstract
A
decision tree
is one of the most popular approaches in machine learning fields. However, it suffers from the problem of
overfitting
caused by overly deepened trees. Then, a
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