Revisiting k-Means: 3 Approaches to Make It Work Better - MachineLearningMastery.com

This tutorial will explore three of the most effective techniques to make k-means work better in the wild, specifically using k-means++ for smarter centroid initialization, leveraging the silhouette score to find the optimal number of clusters, and applying the kernel trick to handle non-spherical data.