K-means clustering is one of the simplest and popular unsupervised machine learning algorithms. K-means algorithm identifies k number of centroids, and then allocates every data point to the nearest cluster, while keeping the centroids as small as possible. A cluster refers to a collection of data points aggregated together because of certain similarities.
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View Code? Open in Web Editor NEWK-means clustering is one of the simplest and popular unsupervised machine learning algorithms. K-means algorithm identifies k number of centroids, and then allocates every data point to the nearest cluster, while keeping the centroids as small as possible. A cluster refers to a collection of data points aggregated together because of certain similarities.
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