An information theoretic feature selection framework based on integer programming

@article{Nie2016AnIT,
  title={An information theoretic feature selection framework based on integer programming},
  author={Siqi Nie and Tian Gao and Qiang Ji},
  journal={2016 23rd International Conference on Pattern Recognition (ICPR)},
  year={2016},
  pages={3584-3589}
}
We propose a general framework for information theoretic feature selection based on the integer programming. Filter feature selection methods usually rely on a greedy forward or backward selection heuristic to find a satisfactory set of features, as the exact search is a combinatorial problem. We formulate the existing filter information theoretic criteria into an integer programming problem, and by using objective functions, we can represent many different existing scoring criteria. The… CONTINUE READING

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