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Malaria Diagnosis System by Using ID3 Classification Algorithm

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dc.contributor.author Thuai, Khaing Mar
dc.contributor.author Thant, Moe
dc.date.accessioned 2019-07-31T06:00:07Z
dc.date.available 2019-07-31T06:00:07Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1495
dc.description.abstract Decision Tree algorithms are the most popular algorithms for classification in data mining field. The main goal of classification is prediction of the categorical labels (classes). In this system, ID3 algorithm is used to predict infection of malaria disease on patients by selecting training data (patients’ medical records), constructing decision model and adjust the model based on testing data (part of patients’ medical records). The constructed model is represented in the form of decision tree and classification rules. The choice of suitable model to predict malaria infection on patient can decide against the correctness of model (classifier accuracy). To get the best classifier accuracy, this system permits selecting no of records to train the system and remove unnecessary braches of tree. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.subject Classification Rule en_US
dc.subject Classifier en_US
dc.subject Classes en_US
dc.subject Data Mining en_US
dc.subject Decision Tree en_US
dc.title Malaria Diagnosis System by Using ID3 Classification Algorithm en_US
dc.type Article en_US

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