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Home / Archives / Volume-4 / Issue-4 / Article-3

Volume - 4 | Issue - 4 | december 2022

Analysis of Classification Algorithms in Drug Classification Using Weka Data Mining Tool
B. Deepthi  , K. V. Siva Prasad Reddy, B. S. Jubedha
Pages: 246-260
Cite this article
Deepthi, B., Reddy, K. V. S. P. & Jubedha, B. S. (2022). Analysis of Classification Algorithms in Drug Classification Using Weka Data Mining Tool. Journal of Trends in Computer Science and Smart Technology, 4(4), 246-260. doi:10.36548/jtcsst.2022.4.003
Published
08 December, 2022
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.

Keywords

Classification J48 Naïve Bayes K-Nearest Neighbour cross validation accuracy correctly classified and incorrectly classified instances.

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