Walle
Created page with "{{see also|Machine learning terms}} ==Introduction== The '''Earth Mover's Distance''' (EMD), also known as the '''Wasserstein distance''' or '''Mallows distance''', is a measure of dissimilarity between two probability distributions in machine learning, statistics, and computer vision. It was originally introduced by Y. Rubner, C. Tomasi, and L.J. Guibas in their 1998 paper titled "A Metric for Distributions with Applications to Image Databases". EMD is especially useful..."
