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Diagnosis of Hypothyroid Disease by Using Decision Tree Induction

http://hdl.handle.net/20.500.12678/0000004183
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bd37568e-afd0-403d-812c-49b4cb3f76e0
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55334.pdf 55334.pdf (270 Kb)
Publication type
Article
Upload type
Publication
Title
Title Diagnosis of Hypothyroid Disease by Using Decision Tree Induction
Language en
Publication date 2009-12-30
Authors
Htut, May Zin
Win, Thin Zar
Description
Data mining is the process of discovering usefulinformation underlying the data. Powerfultechniques are needed to extract patterns from largedata because traditional statistical tools areefficient enough any more. Classification andprediction are two forms of data analysis that canbe used predict future data trends. In this paper, weproposed a diagnosis system for Hypothyroiddisease by using decision tree induction algorithm.Decision tree induction algorithms have been usedfor classification in a wide range of applicationdomains. Decision trees are potentially powerfulpredictors and explicitly represent the structure of adataset. In this system, C4.5 classification algorithmis analyzed to build the model from a given set oftraining data and then produced classification rules.It examines the patient is positive or negative inhypothyroid. The performance evaluation of oursystem is also discussed in this paper.
Keywords
Data mining, Classification, Decision Tree Induction, Cross Validation method
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1879
Journal articles
Fourth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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