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计算机工程 ›› 2006, Vol. 32 ›› Issue (17): 44-47. doi: 10.3969/j.issn.1000-3428.2006.17.016

• 专题论文 • 上一篇    下一篇

一种模糊分类器集成的方法

阳爱民1;胡运发2;周咏梅1   

  1. (1. 湖南工业大学计算机系,株洲 412008;2. 复旦大学计算机与信息技术系,上海 200433)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-09-05 发布日期:2006-09-05

A Classifier Ensemble Method for Fuzzy Classifiers

YANG Aimin1;HU Yunfa2;ZHOU Yongmei1   

  1. (1. Department of Computer Science, Hunan University of Techology, Zhuzhou 412008; . Department of Computer and Information Technology, Fudan University, Shanghai 200433)
  • Received:1900-01-01 Revised:1900-01-01 Online:2006-09-05 Published:2006-09-05

摘要: 提出了一种基于模糊积分的模糊分类器集成的方法,该方法能在模糊分类器生成过程中,进一步减少主观因素的参与成份,使分类模器具有更好的稳定性和更高的分类识别率。给出了基于隶属度矩阵的模糊积分密度确定方法,介绍了基于模糊积分的分类器集成算法。用权威的数据集作为实验数据集,将提出方法与已有的分类器集成方法进行实验比较,评测了所提出方法的有效性。

关键词: 分类器集成, 模糊分类器, 模糊积分, 模糊积分密度

Abstract: A classifier ensemble method with fuzzy integral for fuzzy classifier is proposed. The object of this method is to reduce subjective factor during constructing a fuzzy classifier, and to improve the classification recognition rate and stability for classification system. For this object, a method of determining fuzzy integral density with membership matrix is proposed, and the classifier ensemble algorithm based on fuzzy integral is introduced. The proposed method is evaluated by the comparison of experiments with standard data sets and the existed classifier ensemble methods.

Key words: Classifier ensemble, Fuzzy classifier, Fuzzy integral, Fuzzy integral density

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