A selective sampling approach to active feature selection

@article{Liu2004ASS,
  title={A selective sampling approach to active feature selection},
  author={Huan Liu and Hiroshi Motoda and Lei Yu},
  journal={Artif. Intell.},
  year={2004},
  volume={159},
  pages={49-74}
}
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improving result comprehensibility. Traditional feature selection methods resort to random sampling in dealing with data sets with a huge number of instances. In this paper, we introduce the concept of active feature selection, and investigate a selective sampling approach to active feature selection in a filter model… CONTINUE READING
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