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| Decision Tree Classifiers to determine the patient’s Post-operative Recovery Decision
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Full
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Source |
International Journal of Artificial Intelligence and Expert Systems (IJAE) |
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Table of Contents |
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Complete Issue PDF(487.48KB) |
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Volume: 1 Issue: 4 |
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Pages: 75-122 |
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Publication
Date: December 2010 |
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ISSN
(Online): 2180-124X |
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Pages |
75 - 87 |
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Author(s) |
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Published
Date |
08-02-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: Machine Learning, Data Mining, Decision Tree |
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| This Manuscript is indexed in the following databases/websites:- |
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| 1. Google Scholar |
| 2. Docstoc |
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| Machine Learning aims to generate classifying expressions simple enough to be understood easily by the human. There are many machine learning approaches available for classification. Among which decision tree learning is one of the most popular classification algorithms. In this paper we propose a systematic approach based on decision tree which is used to automatically determine the patient’s post–operative recovery status. Decision Tree structures are constructed, using data mining methods and then are used to classify discharge decisions. |
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| Shanthi Dhanushkodi : Colleagues
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| G.Sahoo : Colleagues
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| Saravanan Nallaperumal : Colleagues
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