In unsupervised machine learning, k-implies clustering might be used to compress data by grouping equivalent data factors into clusters. This method simplifies dealing with extensive datasets that lack predefined labels and finds common use in fields including picture compression.[29]Such as, an algorithm might be fed a scaled-down amount of labele