Citation
Ibrahim, Norul Hidayah and Mustapha, Aida and Rosli, Rozilah and Helmee, Nurdhiya Hazwani
(2013)
A hybrid model of hierarchical clustering and decision tree for rule-based classification of diabetic patients.
International Journal of Engineering and Technology, 5 (5).
pp. 3986-3991.
ISSN 2319-8613; ESSN: 0975-4024
Abstract
Hybrid models in data mining have recently gained attention including in the study of medical research. Various studies in this domain using hybrid models have shown different results. This paper presents the new hybrid model by exploring Agglomerative Hierarchical Clustering and Decision Tree Classifier on Pima Indians Diabetes dataset. The experiments compared performance accuracy of the Decision Tree Classifier against the same classifier augmented with Hierarchical Clustering. Results showed that the hybrid model achieved higher accuracy with 80.8% as compared to 76.9% of the standard model. This is a promising result for adoption of hierarchical clustering in a rule-based classifier.
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Official URL or Download Paper: http://www.enggjournals.com/ijet/vol5issue5.html
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Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Computer Science and Information Technology |
| Publisher: | Engg Journals Publications |
| Keywords: | Medical data mining; Hierarchical clustering; Classification; Decision tree; Hybrid model. |
| Depositing User: | Ms. Nida Hidayati Ghazali |
| Date Deposited: | 02 Jun 2014 02:32 |
| Last Modified: | 21 Sep 2015 03:50 |
| URI: | http://psasir.upm.edu.my/id/eprint/30685 |
| Statistic Details: | View Download Statistic |
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