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Mining association rules for classification using frequent generator itemsets in arules package

Author

Listed:
  • Makhlouf Ledmi
  • Mohammed El Habib Souidi
  • Michael Hahsler
  • Abdeldjalil Ledmi
  • Chafia Kara-Mohamed

Abstract

Mining frequent itemsets is an attractive research activity in data mining whose main aim is to provide useful relationships among data. Consequently, several open-source development platforms are continuously developed to facilitate the users' exploitation of new data mining tasks. Among these platforms, the R language is one of the most popular tools. In this paper, we propose an extension of arules package by adding the option of mining frequent generator itemsets. We discuss in detail how generators can be used for a classification task through an application example in relation with COVID-19.

Suggested Citation

  • Makhlouf Ledmi & Mohammed El Habib Souidi & Michael Hahsler & Abdeldjalil Ledmi & Chafia Kara-Mohamed, 2023. "Mining association rules for classification using frequent generator itemsets in arules package," International Journal of Data Mining, Modelling and Management, Inderscience Enterprises Ltd, vol. 15(2), pages 203-221.
    • Handle: RePEc:ids:ijdmmm:v:15:y:2023:i:2:p:203-221
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