Sunday, December 11, 2011

KMeans and Vector Quantization

KMeans clustering is a type of Vector Quantization ("Since vector quantization is a natural application for k-means, information theory terminology is often used."[1] ).

From Machine Learning perspective, feature vectors can be considered as code-word and the table mapping code-word to cluster ids is a codebook.

Each feature vector to be clustered is considered as a code-word and in KMeans clustering, they are assigned to the closest centroid (cluster id).

Pages describing Vector Quantization - KMeans:

  1. Vector Quantization
  2. Documentation on K-means clustering and VQ in Python
  3. KMeans in OpenCV using C++.

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