An efficient and effective ensemble of support vector machines for anti-diabetic drug failure prediction
We propose a method called E3-SVM, efficient and effective ensemble of SVMs. E3-SVM excludes superfluous data points when constructing an SVM ensemble. E3-SVM was applied to the drug failure prediction problem for type 2 diabetes. We confirmed the suitability of SVM with an accuracy of about 80%.
ensemble support vector machines drug failure prediction type 2 diabetes data selection