The Lloyd-Max quantizer is a scalar quantizer which can be seen as a special case of a vector quantizer (VQ) designed with the Linde Buzo Gray (LBG) algorithm.
In k-means clustering, we are given a set of n data points in d-dimensional space and an integer k and the problem is to determine a set of k points in $R^d$, called centers, so as to minimize the mean squared distance from each data point to its nearest center. A popular heuristic for k-means clustering is Lloyd's (1982) algorithm.
What is the difference between clustering and quantization. I understand the mechanism of clustering technique which is a unsupervised method of grouping data points whereby we map data points into indices of cluster centers which is closest to it. There are different algorithm to perform clustering - Is clustering another way of doing quantization? Quantization are of 2 kinds -scalar and vector. k-means algorithm is applied for vector quantization. Again k-means algorithm is also applied in vector clustering. So, is vector quantization = vector clustering?