Gaussian Mixture Models vs K-Means. Which One to Choose?

Comparing the Performance of Two Popular Clustering Algorithms

G. Mixture vs K. Means (1957). Oil on canvas. No clear winner, btw. Photo by Birmingham Museums Trust on Unsplash

K-Means and Gaussian Mixtures (GMs) are both clustering models. Many data scientist, however, tend to choose a more popular K-Means algorithm. Even if GMs can prove superior in certain clustering problems.