文章基本信息

标题：Building A Bi-objective Quadratic Programming Model for the Support Vector Machine
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作者：Mohammed Zakaria Moustafa ; Mohammed Rizk Mohammed ; Hatem Awad Khater 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2020
卷号：10
期号：2
页码：91-97
DOI：10.5121/csit.2020.100208
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：A support vector machine (SVM) learns the decision surface from two different classes of the inputpoints, in many applications there are misclassifications in some of the input points. In this papera biobjective quadratic programming model is utilized and different feature quality measures areoptimized simultaneously using the weighting method for solving our bi-objective quadraticprogramming problem. An important contribution will be added for the proposed bi-objectivequadratic programming model by getting different efficient support vectors due to changing theweighting values. The experimental results, give evidence of the effectiveness of the weightingparameters on reducing the misclassification between two classes of the input points.
关键词：Support vector machine (SVMs); Classification; Multi;objective problems; weighting;method; Quadratic programming