| 摘要: |
| 自动文本分类是提高信息利用效率和质量的有效方法,而多分类器的有效组合能够得到更高的分类准确率.给出了样本集在多分类器下的全信息矩阵概念,并提出一种权重自适应调整的多分类器集成方法.该方法能够自适应地选择分类器组合及确定分类器权重,并利用分类统计信息指导分类结果的集成判决.通过在标准文本集Reuters-21578上的实验表明:该方法能从查准率和查全率两方面提高文本分类的整体性能,同时表明了该方法的有效性. |
| 关键词: 多分类器组合 全信息矩阵 文本分类 |
| DOI： |
| 分类号: |
| 基金项目:Supported by the Science and Technology Committee of Beijing of China under Grant No.2001-0075 (北京市科委科技项目基金) |
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| A Multiple Classifiers Integration Method Based on Full Information Matrix |
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TANG Chun-Sheng,JIN Yi-Hui
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| Abstract: |
| Automatic text categorization is an effective method to increase the efficiency and quality of information utilizing. The combination of a set of different classifiers can often achieve higher classification accuracy. The concept of full information matrix is first given, and then an integration method of multiple classifiers based on adaptive weight adjusting is presented in this paper. The classifiers and their weights are determined automatically and adaptively with this method. The effective integration of each classifier抯 result can be realized by analyzing the statistical information of the classifier on the training set. The classification performance is promoted by the improvement of the precision and the recall. The effectiveness of the method is shown by the text classification experiments on the Reuters-21578 text sets. |
| Key words: combination of multiple classifiers full information matrix text classification |
