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Classification of Different Abdominal Pain using Decision Tree Induction (ID3 Algorithm)

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dc.contributor.author Myint, Khine Swe
dc.contributor.author Mar, Win
dc.date.accessioned 2019-07-25T08:04:46Z
dc.date.available 2019-07-25T08:04:46Z
dc.date.issued 2011-12-29
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1346
dc.description.abstract Nowadays, data classification techniques are very increasingly and applied in real world domain such as medicine, manufacturing and production, weather prediction, and financial analysis. Data classification is the process of building a model from available data called the training data set and classifying disease according to their attributes. Among the increase in the use of data classification technique, decision tree induction method is one of the most useful method. In this system, presents the classification of acute abdominal pain problems using decision tree induction. Thus, this system intends to provide information for junior medical practitioners and the user who faced abdominal pain. This paper implements the decision tree using ID3 and gives advice to users about the cases acute abdominal pain. This paper calculates the system accuracy by using holdout method and implemented by Java programming language. Jdk1.6 and SQL server 2008. en_US
dc.language.iso en en_US
dc.publisher Sixth Local Conference on Parallel and Soft Computing en_US
dc.title Classification of Different Abdominal Pain using Decision Tree Induction (ID3 Algorithm) en_US
dc.type Article en_US

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