Attribute reduction based on a rapid variable granular ball generation model

HIGHLIGHTS

• What: To address these issues this study introduces new granular ball quality index to judge the separability degree of decision classes and the basis of this index granular ball generation model (RVGBGM) is proposed. The authors compare the RVGBGM algorithm with classical algorithms and the current state-of-the-art granular ball algorithm 11 datasets. The authors provide a detailed illustration of δ(xk ) and δB (xk ) through Example 1, where δB (xk ) represents the δ-neighborhood of xk over the attribute subset B. Example 1. The experiment aims to test the performance of the proposed algorithm (RVGBGM) by . . .
  

   

  

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