In unsupervised machine learning, k-indicates clustering is usually used to compress data by grouping equivalent data details into clusters. This method simplifies handling intensive datasets that lack predefined labels and finds common use in fields like impression compression.[31][136] By refining the mental versions of end users of AI-run progra