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In unsupervised machine learning, k-implies clustering is often used to compress data by grouping very similar data details into clusters. This method simplifies dealing with intensive datasets that deficiency predefined labels and finds common use in fields which include picture compression.[31]Learners may disappoint by "learning the wrong lesson