Why K-Means Fails on Non-Convex Clusters and Alternatives
K-means clustering stands as one of the most popular unsupervised learning algorithms, beloved for its simplicity, speed, and interpretability. From customer segmentation to image compression, k-means has become the default choice when practitioners need to partition data into groups. Yet beneath this widespread adoption lies a fundamental limitation that many overlook until it causes their … Read more