K Means Clustering
K means clustering can yield unexpected results, especially when data doesn't conform to intuitive patterns. The process involves initializing centroids, assigning data points, and recalculating centroids, with the potential for infinite loops if not properly managed. Approaches like k means plus plus offer smarter initialization strategies, emphasizing the need for a critical eye on clustering outcomes.In this clip
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Data Skeptic
k-means clustering
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