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- W2354568153 abstract "A c-SVDD algorithm is proposed based on Support Vector Date Description algorithm.In the c-SVDD algorithm,the C in SVDD with negative sample is redefined as a special C for each sample.The c-SVDD is adapted to solve the problem of classification of imbalanced data.In the condition of guaranteeing the high precision of classification of little samples,the precision of classification of all samples can be improved with this algorithm.This paper verifies the efficiency of algorithm for the artificial data and UCI datasets. Compared c-SVDD with SVDD with negative sample,the average AUC increases 0.14 at least.Compared with AdaBoost,the average recall of positive class increases 40%,and the precision increases 5%." @default.
- W2354568153 created "2016-06-24" @default.
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- W2354568153 date "2008-01-01" @default.
- W2354568153 modified "2023-09-23" @default.
- W2354568153 title "Support vector date description based on clustering distribution" @default.
- W2354568153 hasPublicationYear "2008" @default.
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