Simultaneous feature selection and clustering using mixture models

@article{Law2004SimultaneousFS,
  title={Simultaneous feature selection and clustering using mixture models},
  author={Martin H. C. Law and M{\'a}rio A. T. Figueiredo and Anil K. Jain},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2004},
  volume={26},
  pages={1154-1166}
}
Clustering is a common unsupervised learning technique used to discover group structure in a set of data. While there exist many algorithms for clustering, the important issue of feature selection, that is, what attributes of the data should be used by the clustering algorithms, is rarely touched upon. Feature selection for clustering is difficult because, unlike in supervised learning, there are no class labels for the data and, thus, no obvious criteria to guide the search. Another important… CONTINUE READING

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