What is SVM?
support vector machines (SVMs) are universal constructive machine learning procedures based on statistical learning theory. SVM has been applied in many diverse applications such as pattern recognition, computational biology, and image analysis. The basic concept is that by maximizing the separation between the two classes in a nonlinear feature space, SVM not only reduces the training error but more importantly also achieves better generalization on unseen data.
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