Comparative Study for Analysis the Prognostic in Hepatitis Data: Data Mining Approach
نویسندگان
چکیده
Data mining techniques are widely used in classification and prediction in the field of bioinformatics to analyze biomedical data. The purpose of the study is to investigate and compare (7) different classification algorithms namely, Naive Bayes, Naive Bayes updatable, FT Tree, KStar, J48, LMT, and Neural network for analyzing Hepatitis prognostic data. The results of the classification are accuracy and time. The study concludes that the Naive Bayes classification performance is better than other classification techniques for hepatitis dataset.
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تاریخ انتشار 2013