SVM-based classifier ensembles design with co-operative biology inspired algorithm
Автор: Akhmedova Sh. A., Semenkin E.S.
Журнал: Сибирский аэрокосмический журнал @vestnik-sibsau
Рубрика: Математика, механика, информатика
Статья в выпуске: 1 т.16, 2015 года.
Бесплатный доступ
The meta-heuristic called Co-Operation of Biology Related Algorithms (COBRA) is used for the automated design of a support vector machine (SVM) based classifiers ensemble. Two non-standard schemes, based on the use of the locally most effective ensemble member’s output, are used to infer the ensemble decision. The usefulness of the approach is demonstrated on four benchmark classification problems solved: two bank scoring problems (Australian and German) and two medical diagnostic problems (Breast Cancer Wisconsin and Pima Indians Diabetes). Numerical experiments showed that classifier ensembles designed by COBRA exhibit high performance and reliability for separating instances from different categories. Ensembles of SVM-based classifiers implemented in this way outperform many alternative methods on the mentioned benchmark classification problems.
Support vector machines, ensembles, biology inspired algorithms, classification, optimization
Короткий адрес: https://sciup.org/148177399
IDR: 148177399
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