The maximum distance from the decision boundary area to the nearest test observation.

University of Michigan - Ann Arbor

Maximal margin hyperplanes (AKA optimal separating hyperplanes) are used in order to find which hyperplane would give the greatest separation between output classes. These hyperplanes are found by computing the classifier margin.

SVM Maximal Margin Hyperplanes

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, pp. 3-7). New York: springer.

An Introduction to Statistical Learning with Applications in R

The shortest distance from the separating hyperplane to the nearest test observation.

SVM Margin

SVM Classifier Margin

The hyperplane used to classify data depending on which side observations fall under the maximum margin hyperplane.

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