Decision tree model for classification of fake and genuine banknotes using SPSS Online publication date: Tue, 05-Feb-2019
by Akanksha Upadhyaya; Vinod Shokeen; Garima Srivastava
World Review of Entrepreneurship, Management and Sustainable Development (WREMSD), Vol. 14, No. 6, 2018
Abstract: Counterfeiting is an exhaustive problem smashing extensively, virtually as well as in reality, on each sector all around the world. In order to identify and classify fake and genuine banknote various techniques and models have been proposed and developed. This paper proposes an effective predictive model based on machine learning technique for authentication of banknotes, which can predicts with good accuracy that whether the given banknote is fake or genuine. The decision tree model is built using IBM SPSS tool. The performance measure of the model is done using gain charts and index charts and it is found that proposed decision tree model is good enough for prediction of banknote classification as fake or genuine.
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