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Paper Details
Paper Title
Analysis Of Classifiers Diseases Prediction Using Weka Tool
Authors
  Rikendra,  Deepika
Abstract
Binary classification is the task of classifying the members of a given set of objects into two groups on the basis of whether they have some property or not. A typical binary classification task in health care management could be diagnosis of medical testing to determine if a patient will die or live. We have used HEPITITIES database from UCI Machine Repository. The database is containing 153 instances and 20 attributes on which various binary classifiers have been applied, we have used mainly J48,NB TREE AND AD TREE classifiers. We have compared these algorithms on various parameters of performance evaluation; our focus will be on mainly four parameters namely: precision, sensitivity, accuracy and error rate. For classification task we have used WEKA and TANAGRA data mining tools. The results of experiment show that AD Tree gives a promising classification result on the basis of sensitivity, precision ,error rate and accuracy.
Keywords- Data mining, Weka tools ,Classification
Publication Details
Unique Identification Number - IJEDR1902089Page Number(s) - 470-472Pubished in - Volume 7 | Issue 2 | June 2019DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Rikendra,  Deepika,   "Analysis Of Classifiers Diseases Prediction Using Weka Tool", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.7, Issue 2, pp.470-472, June 2019, Available at :http://www.ijedr.org/papers/IJEDR1902089.pdf
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