Unsupervised Feature Selection Using Feature Similarity

  title={Unsupervised Feature Selection Using Feature Similarity},
  author={Pabitra Mitra and C. A. Murthy and Sankar K. Pal},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.},
ÐIn this article, we describe an unsupervised feature selection algorithm suitable for data sets, large in both dimension and size. The method is based on measuring similarity between features whereby redundancy therein is removed. This does not need any search and, therefore, is fast. A new feature similarity measure, called maximum information compression index, is introduced. The algorithm is generic in nature and has the capability of multiscale representation of data sets. The superiority… CONTINUE READING
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