Work

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

Year: 2017

Type: conference-paper

Abstract: 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.

Source: ITM Web of Conferences

DOI: 10.1051/itmconf/20171002002

Authors: Liliya Demidova, Irina Klyueva

Institutions: Moscow Technological Institute, Ryazan State Radio Engineering University

Language: English

Topic: Imbalanced Data Classification Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W2605958366

FWCI: 0.771

Cites: 8

Cited by: 19

Related to: 10