Optimization-based feature selection with adaptive instance sampling

  title={Optimization-based feature selection with adaptive instance sampling},
  author={Jaekyung Yang and Sigurdur {\'O}lafsson},
  journal={Computers & OR},
Preprocessing the data to filter out redundant and irrelevant features is one of the most important steps in the data mining process. Careful feature selection may improve both the computational time of inducing subsequent models and the quality of those models. Using fewer features often leads to simpler and easier to interpret models, and selecting important feature can lead to important insights into the application. The feature selection problem is inherently a combinatorial optimization… CONTINUE READING
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