Choosing a spectacular feature selection technique for telecommunication industry using fuzzy TOPSIS MCDM

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Sampling and Feature Selection may be employed to depreciate processing time and hence diminishing discovery time of churn customer in the telecommunication industry. This article intends to evaluate the feature selection methods based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) ranking method. An Entropy-based TOPSIS method has used to recommend the one or more selections between choices, having multiple attributes. The five Ranking feature selection methods like Information Gain, Gain Ratio, Chi-Square, ReliefF and Fisher score are utilized to decrease the size of the telecommunication dataset. The classification technique like Artificial Neural Network, Naïve Bayes and Support Vector Machine are applied to determine the performance of the feature selection techniques. This Entropy-based TOPSIS method is utilized to examine and rank the feature selection methods to improve the churn customer prediction.

     

     


  • Keywords


    Feature Selection; Information Gain; Gain Ratio; Chi-Square Analysis; Relieff; Fisher; ANN; NB; SVM; Fuzzy TOPSIS.

  • References


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Article ID: 14875
 
DOI: 10.14419/ijet.v7i4.14875




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