Soft Margin SVM is a variant of the support vector machine classifier that permits misclassification of training instances by introducing slack variables to balance margin maximization and classification error minimization in non-linearly separable datasets.
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Marti A. Hearst, Susan Dumais, E. Osuna et al. · IEEE Intelligent Systems and their Applications · 1998 · 6.9K citations
Making Large-Scale SVM Learning Practical
Thorsten Joachims · Technical reports · 2006 · 4.3K citations · Full text
Improvements to Platt's SMO Algorithm for SVM Classifier Design
S. Sathiya Keerthi, Shirish Shevade, Chiranjib Bhattacharyya et al. · Neural Computation · 2001 · 1.8K citations
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