Integration of dense subgraph finding with feature clustering for unsupervised feature selection ?
Unsupervised feature selection approach using densest finding approach followed by feature clustering. Usage of normalized mutual information scores for computing similarity as well as dissimilarity. Superiority over three existing methods is established for eight data sets.
unsupervised feature selection normalized mutual information mutual information pattern recognition