Multi-Label Feature Selection using Correlation Information

@inproceedings{Braytee2017MultiLabelFS,
  title={Multi-Label Feature Selection using Correlation Information},
  author={Ali Braytee and Wei Liu and Daniel R. Catchpoole and Paul J. Kennedy},
  booktitle={CIKM},
  year={2017}
}
High-dimensional multi-labeled data contain instances, where each instance is associated with a set of class labels and has a large number of noisy and irrelevant features. Feature selection has been shown to have great benefits in improving the classification performance in machine learning. In multi-label learning, to select the discriminative features… CONTINUE READING