Performance Analysis of Various Data Mining Techniques on Banknote Authentication

In this paper, we describe the functionality features for authenticating in Euro banknotes. We applied different data mining algorithms such as KMeans, Naive Bayes, Multilayer Perceptron, Decision trees (J48), and Expectation-Maximization(EM) to classifying banknote authentication dataset. The experiments are conducted in WEKA. The goal of this project is to obtain the higher authentication rate in banknote classification.