A feature group weighting method for subspace clustering of high-dimensional data

@article{Chen2012AFG,
  title={A feature group weighting method for subspace clustering of high-dimensional data},
  author={Xiaojun Chen and Yunming Ye and Xiaofei Xu and Joshua Zhexue Huang},
  journal={Pattern Recognition},
  year={2012},
  volume={45},
  pages={434-446}
}
This paper proposes a new method to weight subspaces in feature groups and individual features for clustering high-dimensional data. In this method, the features of high-dimensional data are divided into feature groups, based on their natural characteristics. Two types of weights are introduced to the clustering process to simultaneously identify the importance of feature groups and individual features in each cluster. A new optimization model is given to define the optimization process and a… CONTINUE READING