期刊刊名：管理科學與統計決策 　 卷期：7卷1期

篇名出版日期：2010年3月1日

作者：Lei Yang,Wei-Min Ma, Bo Tian

語言：English

關鍵字：support vector domain description,twin support vector domain description,relative distance,pattern classification

被點閱次數：0次

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摘要：
Twin support vector domain description(Twin-SVDD) classifier with the conception of relative distance was proposed in this paper. The preliminary SVDD model described the target dataset with one class by constructing a compact optimized hypersphere in feature space. And the model was effective to deal with problems of pattern classification with imbalanced dataset such as outlier detection. But only information about the positive class of dataset was used in the preliminary SVDD model. As for binary classification problem, inspired by the construction of Twin support vector machine where nonparallel planes were solved separately, the Twin-SVDD model was proposed. Two optimized hyperspheres which described positive and negative class of datasets were constructed separately in the Twin-SVDD model. So information about both classes of dataset was used. And then new classification decision-making function was constructed based on the parameters of the Twin-SVDD model with the conception of relative distance. At last, experiments were performed. Experimental results showed that the Twin-SVDD model was more effective than the preliminary SVDD model when dealing with pattern classification problems. And the proved classification decision-making function improved the performance of the Twin-SVDD model.

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