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This process condenses substantial datasets into a additional compact list of consultant factors. Notably beneficial in image and signal processing, k-suggests clustering aids in data reduction by replacing teams of data factors with their centroids, thereby preserving the Main data of the initial data when appreciably lowering the required storage