6 Factors That Makes K-Means a Popular Clustering Algorithm

Scalability, Pre-Clustering, and Many More

Photo by Ellen Qin on Unsplash

K-means clustering isn’t the best clustering algorithm out there. It isn’t highly accurate because K-means assumes all clusters to be even in size and spherical in shape. K-means also can’t handle complex geometry. It is specifically useful only for flat geometry clusters. And outliers, if…

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I am curious about product innovation, AI and noteworthy ideas.