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Updated: Apr 15, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
[Comparative efficiency of algorithms based on support vector machines for binary classification]
Abstract:
Methods of construction of support vector machines require no further a priori infoimation and provide big data processing, what is especially important for various problems in computational biology. The question of the quality of learning algorithms is considered. The main algorithms of support vector machines for binary classification are reviewed and they were comparatively explored for their efficiencies. The critical analysis of the results of this study revealed the most effective support-vector-classifiers. The description of the recommended algorithms, sufficient for their practical implementation, is presented.
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