In unsupervised machine learning, k-usually means clustering can be used to compress data by grouping related data factors into clusters. This technique simplifies dealing with comprehensive datasets that lack predefined labels and finds widespread use in fields which include impression compression.[29]Systems which are trained on datasets gathered