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An improvement of least square - twin support vector machine
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In this paper, we propose a new Improvement Least Square - Support Vector Machine (called ILS-SVM) for binary classification problems with a class-vs-cluster strategy. Experimental results show that the ILS-SVM training time is faster than that of TSVM, and the ILS-SVM accuracy is better than LSTSVM and TSVM in most cases.
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