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'''Vector quantization''' is a classical [[quantization]] technique from [[signal processing]] which allows the modeling of probability density functions by the distribution of prototype vectors. It was originally used for [[data compression]]. It works by dividing a large set of points ([[coordinate vector|vector]]s) into groups having approximately the same number of points closest to them. Each group is represented by its [[centroid]] point, as in [[k-means]] and some other [[clustering]] algorithms.
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