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Erschienen in:
2016 | OriginalPaper | Buchkapitel
4. Linear Support Vector Machines
verfasst von : M. N. Murty, Rashmi Raghava
Erschienen in: Support Vector Machines and Perceptrons
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Abstract
Support vector machine (SVM) is the most popular classifier based on a linear discriminant function. It is ideally suited for binary classification. It has been studied extensively in several pattern recognition applications and in data mining. It has become a baseline standard for classification because of excellent software packages that have been developed systematically over the past three decades. In this chapter, we introduce SVM-based classification and some of the essential properties related to classification. Specifically we deal with linear SVM that is ideally suited to deal with linearly separable classes.