Abstract
Classification algorithms have been found to produce better results in terms of performance and accuracy, when used with drug observation dataset. Three machine learning algorithms such as J48, Naive Bayes, and K-Nearest Neighbor are compared using Waikato Environment for Knowledge Analysis (WEKA) in this paper. In addition, these three well-known classification methods are evaluated based on different Quality of Service parameters to find the best fit classifier for the design of the model. The analysis procedure of dataset and the performance indicators are discussed. These results help to draw a conclusion about which of the three algorithms is the best for drug classification.
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