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What is K-means clustering?
by Diamond (53,882 points) | 15 views

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K-means clustering aims to partition a set of observations into K clusters, resulting in the partitioning of the data into groups. It starts by placing K central positions (centroids) in random locations in the multidimensional (Euclidian) space. It then uses the Euclidean distance between data points and centroids to assign each data point to the cluster that is closest. The process is iterative
by Diamond (53,882 points)

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