K-means Clustering
K-means clustering is a type of unsupervised learning algorithm used in data science and artificial intelligence to group similar data points together. The algorithm works by partitioning a dataset into k clusters, where k is a predefined number chosen by the user. The algorithm then iteratively assigns each data point to the nearest cluster centroid and recalculates the centroid of each cluster until the centroids no longer move or a maximum number of iterations is reached. K-means clustering is commonly used in data mining, image processing, and market segmentation.
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