Do all roads lead to Rome? Studying distance measures in the context of machine learning.

•Review of the most commonly used distance measures in machine learning•Analysis of their main properties, applications and key aspects to consider•The similarity analysis shows a high degree of correlation between all the measures•Evaluation of classification and clustering performance, noise tolerance and runtime•Canberra distance shows the best overall performance and the highest tolerance to noise