Support Vector Machines for Classification

Science is the systematic classification of experience.

—George Henry Lewes

This chapter covers details of the support vector machine (SVM) technique, a sparse kernel decision machine that avoids computing posterior probabilities when building its learning model. SVM offers a principled approach to machine learning problems because of its mathematical foundation in statistical learning theory. SVM constructs its solution in terms of a subset of the training input. SVM has been extensively used for classification, regression, novelty detection tasks, and feature reduction. This chapter focuses ...

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