BASSUM: A Bayesian semi-supervised method for classification feature selection

@article{Cai2011BASSUMAB,
  title={BASSUM: A Bayesian semi-supervised method for classification feature selection},
  author={Ruichu Cai and Zhenjie Zhang and Zhifeng Hao},
  journal={Pattern Recognition},
  year={2011},
  volume={44},
  pages={811-820}
}
Feature selection is an important preprocessing step for building efficient, generalizable and interpretable classifiers on high dimensional data sets. Given the assumption on the sufficient labelled samples, the Markov Blanket provides a complete and sound solution to the selection of optimal features, by exploring the conditional independence relationships among the features. In real-world applications, unfortunately, it is usually easy to get unlabelled samples, but expensive to obtain the… CONTINUE READING

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