ITM Web Conf.
Volume 10, 20172017 Seminar on Systems Analysis
|Number of page(s)||4|
|Published online||15 March 2017|
Improving the Classification Quality of the SVM Classifier for the Imbalanced Datasets on the Base of Ideas the SMOTE Algorithm
1 Moscow Technological Institute, 119334 Moscow, Russia
2 State Radio Engineering University, 390005 Ryazan, Russia
* Corresponding author: firstname.lastname@example.org
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.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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