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May, 2015
DART:Dropouts meet Multiple Additive Regression Trees
DART: Dropouts meet Multiple Additive Regression Trees
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K. V. Rashmi, Ran Gilad-Bachrach
TL;DR
本文提出一种新的利用Dropouts工具的方法,称为DART算法,用于解决多个回归树的集成模型中存在的过度特化问题,实验结果表明DART算法在排名、回归和分类任务中表现出优异的性能,并且在很大程度上克服了过度特化的问题。
Abstract
multiple additive regression trees
(MART), an ensemble model of
boosted regression trees
, is known to deliver high prediction accuracy for diverse tasks, and it is widely used in practice. However, it suffers an
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