A brief conceptual view on classification using support vector machine

Abstract

Classifier is an important element for a classification process to classify features or samples of a dataset successfully. The existence of classifier is important, especially involved multiple class dataset with huge number of features or samples. Support Vector Machine (SVM) classifier catches more attention over other classifiers as it is widely used in various fields. Therefore, this paper aims to give a brief conceptual view of SVM in classification. The important elements and principle of SVM are also described. Along with that an appropriate evaluation and validation for SVM performance are also included. As a result, SVM concept in solving real world classification problem is identified for future reference.