Support Vector Machine Using A Classification Algorithm

Nurul Huda Ovirianti, Muhammad Zarlis, Herman Mawengkang

2022SinkrOn15 citationsDOI Open Access PDF

Abstract

Support vector machine is a part of machine learning approach based on statistical learning theory. Due to the higher accuracy of values, Support vector machines have become a focus for frequent machine learning users. This paper will introduce the basic theory of the Support vector machine, the basic idea of classification and the classification algorithm for the support vector machine that will be used. Solving the problem will use an algorithm, and prove the effectiveness of the algorithm on the data that has been used. In this study, the support vector machine has obtained very good accuracy results in its completion. The SVM classification uses kernel RBF with optimum parameters Cost = 5 and gamma = 2 is 88%.

Topics & Concepts

Support vector machineRelevance vector machineStructured support vector machineMachine learningStatistical learning theoryArtificial intelligenceComputer scienceAlgorithmRanking SVMKernel methodLeast squares support vector machineKernel (algebra)Statistical classificationComputational learning theoryStability (learning theory)MathematicsCombinatoricsAdvanced Algorithms and ApplicationsFace and Expression Recognition