Proposal for Measuring Quality of Decision Trees Partition
| Autor: | Abdelkader Adla, Souad Taleb Zouggar |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
General Computer Science
Computer science 05 social sciences Decision tree 02 engineering and technology computer.file_format computer.software_genre 050105 experimental psychology Modeling and Simulation 0202 electrical engineering electronic engineering information engineering Partition (number theory) 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Data mining computer ID3 |
| Zdroj: | International Journal of Decision Support System Technology. 9:16-36 |
| ISSN: | 1941-630X 1941-6296 |
| DOI: | 10.4018/ijdsst.2017100102 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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