Improving the Classification Quality of the SVM Classifier for the Imbalanced Datasets on the Base of Ideas the SMOTE Algorithm

被引:8
作者
Demidova, Liliya [1 ,2 ]
Klyueva, Irina [2 ]
机构
[1] Moscow Technol Inst, Moscow 119334, Russia
[2] State Radio Engn Univ, Ryazan 390005, Russia
来源
2017 SEMINAR ON SYSTEMS ANALYSIS | 2017年 / 10卷
关键词
D O I
10.1051/itmconf/20171002002
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The approach to the classification problem of the imbalanced datasets has been considered. The aim of this research is to determine the effectiveness of the SMOTE algorithm, when it is necessary to improve the classification quality of the SVM classifier, which is applied for classification of the imbalanced datasets. The experimental results which demonstrate the improvement of the SVM classifier quality with application of ideas the SMOTE algorithm for the imbalanced datasets in the sphere of medical diagnostics have been given.
引用
收藏
页数:4
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