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J4 ›› 2010, Vol. 45 ›› Issue (7): 7-12.

• 论文 • 上一篇    下一篇

产生式与判别式组合分类器学习算法

江雪莲,石洪波*   

  1. 山西财经大学信息管理学院, 山西 太原 030006
  • 收稿日期:2010-04-02 出版日期:2010-07-16 发布日期:2010-09-06
  • 通讯作者: 石洪波(1965-),女,教授,博士,研究方向为数据挖掘、机器学习.
  • 作者简介:江雪莲(1985-),女,硕士研究生,研究方向为数据挖掘、机器学习.Email:xuelianjiang@126.com
  • 基金资助:

    国家自然科学基金资助项目(60873100);山西省自然科学基金资助项目(2009011017-4)

The learning algorithm of a generative and discriminative combination classifier

JIANG Xue-lian, SHI Hong-bo*   

  1. Department of Information Management, Shanxi University of Finance & Economics, Taiyuan 030006, Shanxi, China
  • Received:2010-04-02 Online:2010-07-16 Published:2010-09-06

摘要:

在AdaBoost集成方法的基础上,研究了一种产生式与判别模型组合的方法。该算法在每轮中同时学习一个产生式分类器和一个判别式分类器,选择误差率较小的作为个体分类器,然后对所有个体分类器采用加权的方法得到最终分类器。实验结果表明,该方法在准确率和收敛速度上都得到了很好的效果。

关键词: 产生式模型;判别式模型;集成分类器;个体分类器

Abstract:

Based on the AdaBoost ensemble framework,  a learning algorithm of generative/discriminative combination classifier was proposed. In each round of the algorithm, a generative classifier and a discriminative classifier were learned, and the classifier with the smaller error rate was selected as the individual classifier, and then all the individual classifiers were combined by a weighted approach. Experiment results showed  that this method was very good on accuracy and convergence speed.
 

Key words: generative models; discriminative models; ensemble classifier; individual classifier

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