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Proposal for Measuring Quality of Decision Trees Partition

Author

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  • Souad Taleb Zouggar

    (University of Oran 2, Department of Economics, Oran, Algeria)

  • Abdelkader Adla

    (University of Oran 1, Department of Computer Science, Oran, Algeria)

Abstract

To compute a partition quality for a decision tree, we propose a new measure called NIM “New Information Measure”. The measure is simpler, provides similar performance, and sometimes outperforms the existing measures used with tree-based methods. The experimental results using the MONITDIAB application (Taleb & Atmani, 2013) and datasets from the UCI repository (Asuncion & Newman, 2007) confirm the classification capabilities of our proposal in comparison to the Shannon measure used with ID3 and C4.5 decision tree methods.

Suggested Citation

  • Souad Taleb Zouggar & Abdelkader Adla, 2017. "Proposal for Measuring Quality of Decision Trees Partition," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 9(4), pages 16-36, October.
    • Handle: RePEc:igg:jdsst0:v:9:y:2017:i:4:p:16-36
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