Željko Đ Vujović

Publications

• Case Report   
  A Case Study of the Application of WEKA Software to Solve the Problem of Liver Inflammation
  Author(s): Željko Đ Vujović*
  
  This paper aimed to consider the reliability of the basic metrics of evaluation of classification models: accuracy, sensitivity, specificity, and precision. The WEKA software tool was applied to the “Hepatitis C Virus (HCV) for Egyptian patient’s dataset”. The algorithms Bayesnet, Naivebayesh, Multilayer Perceptron, J48, and 10-fold crossvalidation were used in the study. The main results obtained are that, with all four algorithms in question, they achieved approximately the same accuracy of correctly classified specimens. BaiesNet-22.96%, Naïve Baies-26.14%, MultilaierPerceptron -26.57% and J48-25.27%. Binary classification metrics-sensitivity, specificity, and precision show very different values, depending on the intended class. Metric specificity, for all four algorithms, shows that a value that is in most of the range of possible.. Read More»
  

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