Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy

@article{Peng2005FeatureSB,
  title={Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy},
  author={H. Peng and Fuhui Long and C. Ding},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2005},
  volume={27},
  pages={1226-1238}
}
  • H. Peng, Fuhui Long, C. Ding
  • Published 2005
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first derive an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection. Then, we present a two-stage feature selection algorithm by… Expand
On some aspects of minimum redundancy maximum relevance feature selection
Nearest neighbor estimate of conditional mutual information in feature selection
Class-specific mutual information variation for feature selection
Mutual information criterion for feature selection from incomplete data
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 35 REFERENCES
Wrappers for Feature Subset Selection
Input Feature Selection by Mutual Information Based on Parzen Window
  • Nojun Kwak, C. Choi
  • Mathematics, Computer Science
  • IEEE Trans. Pattern Anal. Mach. Intell.
  • 2002
Selection of Relevant Features in Machine Learning
A comparison of methods for multiclass support vector machines
Feature selection for high-dimensional genomic microarray data
Minimum redundancy feature selection from microarray gene expression data
  • C. Ding, H. Peng
  • Biology, Computer Science
  • Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003
  • 2003
Statistical Pattern Recognition: A Review
How Many Genes are Needed for a Discriminant Microarray Data Analysis
Statistical Pattern Recognition
  • J. Davis
  • Computer Science
  • Technometrics
  • 2003
Improved Gene Selection for Classification of Microarrays
...
1
2
3
4
...