Diagnosis of breast cancer using flexible pinball loss support vector machine

Anuradha Kumari, Mushir Akhtar, Muhammad Tanveer, Mohd. Arshad

Abstract: Highlights•A novel convex flexible pinball loss SVM (FP-SVM) is proposed for classification.•The proposed FP-SVM employs two parameters to control the loss on both incorrectly and correctly classified samples.•Numerical experiments on 30 benchmark datasets demonstrate that the proposed FP-SVM outperforms the baseline models.•The proposed model has an application in classifying breast cancer dataset (BreakHis).