The article deals with the problem of predicting changes in the average dispensed amounts, which is the important factor not only for planning the optimal route scheme for the Bank's cash logistics units, but also for ensuring uninterrupted ATM operation. It is proposed to use the Random Forest algorithm to analyze the data, build and select the best model. The best developed model predicts the amount of the average daily cash withdrawals with a pretty high probability of 79.8%. Based on the results obtained it is concluded that the model built on the basis of a Random Forest algorithm (Random Forest Regressor) can act as an efficient tool that improves the quality of logistics of cash in ATMs.
CITATION STYLE
Malysheva, T. A., Panachev, A. A., Medvedeva, M. A., & Kazakova, E. I. (2019). Application of random forest algorithm to predict the average issued amounts in ATMs. In AIP Conference Proceedings (Vol. 2186). American Institute of Physics Inc. https://doi.org/10.1063/1.5137947
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