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Bank note authentication using decision tree rules and machine learning techniques

Banknotes are currencies used by any nation to carry-out financial activities and are every countries asset which every nation wants it (bank-note) to be genuine. Lot of miscreants induces fake notes into the market which resemble exactly the original note. Hence, there is a need for an efficient authentication system which predicts accurately whether the given note is genuine or not. Exhaustive experiments have been conducted using different machine learning techniques and found that Decision tree and MLP techniques are effective for banknote authentication which efficiently classifies a given banknote data. The rules given by Decision Tree are also tested and found that they are accurate enough to be used for prediction.