Attribute relevance in multiclass data sets using the naive Bayes rule

@article{Sotoca2004AttributeRI,
  title={Attribute relevance in multiclass data sets using the naive Bayes rule},
  author={Jos{\'e} Mart{\'i}nez Sotoca and Jos{\'e} Salvador S{\'a}nchez and Filiberto Pla},
  journal={Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.},
  year={2004},
  volume={3},
  pages={426-429 Vol.3}
}
Feature selection using the naive Bayes rule is presented for the case of multiclass data sets. In this paper, the EM algorithm is applied to each class projected over the features in order to obtain an estimation of the class probability density function. A matrix of weights per class and feature is then obtained, where it collects the level of relevance of each feature for the different classes. We show different ways to extract this information and compare the behavior of the ranking of… CONTINUE READING

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