Feature selection of unbalanced breast cancer data using particle swarm optimization

HIGHLIGHTS

• who: Breast cancer and collaborators from the Department Information Systems, Faculty of Computers and Informatics, Suez Canal University have published the Article: Feature selection of unbalanced breast cancer data using particle swarm optimization, in the Journal: (JOURNAL) of Jul/27,/2021
• what: The first two are the core of the approach proposed in the present article. To validate the feature subset selected by IBPSO, the authors compare the results of IBPSO with five related SI algorithms namely, ACO, BCO, CO, BSA and EHO, using 10-fold cross-validation as shown in Table 2 and Table . . .
  

   

  

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