Differentiating distance metrics

It is crucial to capture the subtle differences between the manhattan, euclidean and Minkowski distance metrics. Using them correctly ensures the optimal performance of outlier classifiers on various datasets.

Remember from the formula that changing the parameter p will switch between euclidean, manhattan and other degrees of the Minkowski distance.