| 一种选择性SER-BagBoosting Trees集成学习研究 |
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| 引用本文： | 陈凯,马景义. 一种选择性SER-BagBoosting Trees集成学习研究[J]. 计算机科学, 2009, 36(9): 208-210 |
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| 作者姓名： | 陈凯 马景义 |
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| 作者单位： | 1. 中国人民大学统计学院,北京,100872;中国工商银行总行管理信息部,北京,100000
2. 中央财经大学统计学院,北京,100081 |
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| 基金项目： | 国家自然科学基金重点项目，教育部重点基地重大项目，中财121人才工程青年博士发展基金，全国统计科学研究计划项目，教育部人文社会科学研究项目基金 |
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| 摘 要： | 集成学习已成为机器学习研究的一大热点.提出了一种综合Bagging和Boosting技术特点,以分类回归树为基学习器构造一种新的相似度指标用于聚类并利用聚类技术和贪婪算法进行选择性集成学习的算法--SER-BagBoosting Trees算法.算法主要应用于回归问题.实验表明,该算法往往比其它算法具有更好的泛化性能和更高的运行效率.
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| 关 键 词： | 分类回归树 自助法 选择性集成 |
| 收稿时间： | 2008-10-21 |
| 修稿时间： | 2009-05-15 |
Study of a Selective Ensemble Algorithm Named SER-BagBoosting Trees |
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| CHEN Kai,MA Jing-yi. Study of a Selective Ensemble Algorithm Named SER-BagBoosting Trees[J]. Computer Science, 2009, 36(9): 208-210 |
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| Authors: | CHEN Kai MA Jing-yi |
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| Affiliation: | School of Statistics;Renmin University of China;Beijing 100872;China;Department of Management Information;ICBC;Beijing 100000;China;School of Statistics;Central University of Finance and Economics;Beijing 100081;China |
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| Abstract: | Ensemble learning now becomes much popular in the field of machine learning.This paper introduced a new ensemble algorithm,SER-BagBoosting Trees ensemble algorithm,which was a combination of tree predictors and was based on variational similarity cluster technology and greedy method,and it was also combined with the features of Boosting and Bagging.Compared with a series of other learning algorithms,it often has better generalization ability and higher efficiency. |
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| Keywords: | CART Bootstrap Selective ensemble |
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