In the context of support vector machines, the margin refers to the distance between the closest data points of different classes and the decision boundary that separates them. A larger margin implies a better separation between classes, which often leads to a more robust model. The goal of a support vector machine is to maximize this margin, as it enhances the model's ability to generalize to unseen data.
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