Survey on Noise Estimation and Removal Methods through SVM

Abstract

The Support vector machine is statistical learning method but it is also recognized as another approach to solve and simplify data classification. SVM have been discovered as one of the successful classification techniques for many areas and application and it works on different datasets and gives appropriate result. There is a noise or irrelevant data present in datasets which leads to poor result so to remove those meaningless data some approaches are introduced for better result. In this paper an introduction of SVM (Support Vector Machine) and various noise estimation and noise removal methods based on support vector machine is presented.