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  • Machine Learning in Java
  • AshishSingh Bhatia Bostjan Kaluza
  • 94字
  • 2021-06-10 19:29:57

Euclidean distances

In Euclidean space, with the n dimension, the distance between two elements is based on the locations of the elements in such a space, which is expressed as p-norm distance. Two commonly used distance measures are L2- and L1-norm distances.

L2-norm, also known as Euclidean distance, is the most frequently applied distance measure that measures how far apart two items in a two-dimensional space are. It is calculated as follows:

L1-norm, also known as Manhattan distance, city block distance, and taxicab norm, simply sums the absolute differences in each dimension, as follows:

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