Convex hull ensemble machine

被引：0

作者：

Kim, YD ^{[1
]}

机构：

[1] Ewha Womans Univ, Dept Stat, Seoul, South Korea

来源：

2002 IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS | 2002年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a new ensemble algorithm called "Convex Hull Ensemble Machine (CHEM)." CHEM in Hilbert space is developed first and it is modified to regression and classification problems. Empirical studies show that in classification problems CHEM has similar prediction accuracy as AdaBoost, but CHEM is much more robust to output noise. In regression problems, CHEM works competitively with other ensemble methods such as Gradient Boost and Bagging.

引用

页码：243 / 249

页数：7

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