OWA BASED INFORMATION FUSION TECHNIQUES FOR CLASSIFICATION PROBLEM

摘要：

In this paper, we fusion multi-attribute data into the aggregated values of single attribute by OWA operators, and cluster the aggregated values for classification tasks.The proposed method is consisted of four steps: (1) use stepwise regression to selection the important attribute, (2) utilize OWA operator to get aggregated values of single attribute from multi-attribute data, (3) cluster the aggregated values by K-Means method, (4) predict the testing datas classes.For verifying, we use two dataset to illustrate the proposed method, and compare with the listing methods.The datasets, one is Iris dataset; the other is Wisconsin-breast-cancer dataset.At last, the result shows that the proposed method is better than the listing methods.

关键词： OWA Clustering Information fusion techniques

作者: CHING-HUSE CHENG JING-WEI LIU MING-CHANG WU

作者单位: Department of Information Management, National Yunlin University of Science and Technology, 123, section 3, University Road, Touliu, Yunlin 640, Taiwan, R.O.C.

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 1383-1388

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）