In my previous post https://statcompute.wordpress.com/2019/02/03/sobol-sequence-vs-uniform-random-in-hyper-parameter-optimization/, I’ve shown the difference between the uniform pseudo random and the quasi random number generators in the hyper-parameter optimization of machine learning. Latin Hypercube Sampling (LHS) is another interesting way to generate near-random sequences with a very simple idea. Let’s assume that we’d like to perform LHS for 10 data …