Cost-sensitive feature selection of numeric data with measurement errors

HIGHLIGHTS

• who: Hong Zhao and collaborators from the Laboratory of Granular Computing, Zhangzhou Normal University, Zhangzhou, China have published the research work: Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors, in the Journal: (JOURNAL) of 24/Dec/2012
• what: The aim of feature selection is to reduce the dimensionality of the feature space and to improve the predictive accuracy of a classification algorithm . The authors propose the cost-sensitive feature selection problem of numerical data with measurement errors and deal with it through considering the trade-off between test costs and misclassification costs. The . . .
  

   

  

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