Hands-On Machine Learning with C++

Chebyshev distance

Chebyshev distance can be useful when we need to classify two objects as different when they differ only by one of the coordinates. Here is the formula for Chebyshev distance:

The following diagram displays the differences between the various distances:

We can see that Manhattan distance is the sum of the distances in both dimensions, like walking along city blocks. Euclidean distance is just the length of a straight line. Chebyshev distance is a more flexible alternative to Manhattan distance because diagonal moves are also ...