Comparative Analysis of Data Mining Classification Algorithms in Type-2 Diabetes Prediction Data Using WEKA Approach

The goal of this paper discusses about different types of data mining classification algorithms accuracies that are widely used to extract significant knowledge from huge amounts of data. Here illustrate 20 classifications of supervised data mining algorithms base on type-2 diabetes disease dataset...

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Auteurs principaux:	Kawsar Ahmed, Tasnuba Jesmin
Format:	Artigo
Langue:	Inglês
Publié:	Diponegoro University 2014-10-01
Collection:	International Journal of Science and Engineering
Sujets:	Accuracy Classification Algorithms Confusion Matrix Data Mining Error Rate Type-2 Diabetes in Bangladesh WEKA toolkit
Accès en ligne:	https://ejournal.undip.ac.id/index.php/ijse/article/view/7197
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