Proposal for Measuring Quality of Decision Trees Partition

Souad Taleb Zouggar and Abdelkader Adla
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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

International Journal of Decision Support System Technology (IJDSST), 2017, vol. 9, issue 4, 16-36

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.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jdsst0:v:9:y:2017:i:4:p:16-36

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