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This process condenses comprehensive datasets right into a much more compact set of consultant factors. Specially valuable in image and signal processing, k-implies clustering aids in data reduction by replacing teams of data factors with their centroids, therefore preserving the core facts of the first data whilst noticeably lowering the needed cu