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- W2361833264 abstract "A multi-class support vector machine(SVM)algorithm was introduced based on data relationship(DR-SVM).Through extracting redundant information of subclassifiers based on relationship between different class data(such as inner product of vectors and so on),the DR-SVM model can reduce the number of subclassifiers.Then the multi-classifiers can be trained by traditional SVM.In so doing,the obtained model can be simplified and the satisfactory generalization performance can be reached at same time.The experiment results on benchmark datasets demonstrate that comparing with several traditional multi-class SVM approaches,the DR-SVM possesses better performance.Especially,it is more efficient for some data processing problems like the predicting precision of individual class should be not under a threshold." @default.
- W2361833264 created "2016-06-24" @default.
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- W2361833264 date "2012-01-01" @default.
- W2361833264 modified "2023-09-28" @default.
- W2361833264 title "A Multi-Classification SVM Algorithm Based on Data Relationship" @default.
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