Robust statistical distances for machine learning | Datadog

What this post added

This post introduces and explains the implementation of robust statistical distances for machine learning, focusing on their application in outlier and anomaly detection. It includes interactive visualizations using D3.js to compare various probability distributions and calculate metrics such as Kolmogorov-Smirnov Distance, Earth Mover's Distance, and Cramér-von Mises Distance. The post provides code examples for generating samples from different distributions and calculating these distances.