Data intensive parallel feature selection method study

  title={Data intensive parallel feature selection method study},
  author={Zhanquan Sun and Zhao Li},
  journal={2014 International Joint Conference on Neural Networks (IJCNN)},
Feature selection is an important research topic in machine learning and pattern recognition. It is effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improving result comprehensibility. With the development of computer science, data deluge occurs in many application fields. Classical feature selection method is out of work in processing large-scale dataset because of expensive computational cost. This paper mainly concentrates on the study of data… CONTINUE READING
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