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In unsupervised machine learning, k-means clustering might be utilized to compress data by grouping similar data points into clusters. This technique simplifies dealing with comprehensive datasets that absence predefined labels and finds prevalent use in fields like picture compression.[31]Gaussian processes are well-known surrogate products in Bay

In unsupervised machine learning, k-implies clustering is often used to compress data by grouping very similar data points into clusters. This technique simplifies dealing with substantial datasets that lack predefined labels and finds popular use in fields for example impression compression.[31]In machine learning, whilst working with scikit learn