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

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 i...

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Bibliographic Details
Published in:ITM Web of Conferences 2017, Vol.10, p.2002
Main Authors: Demidova, Liliya, Klyueva, Irina
Format: Article
Language:English
Subjects:
Algorithms
Classification
Classifiers
Datasets
Support vector machines
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Summary: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.
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20171002002