Enhancement of Consumption Forecasting by Customers’ Behavioral Predictability Segregation
Author:
Affiliation:
1. Department of Digital Transformation, ITMO University, St. Petersburg 197101, Russia
2. National Center for Cognitive Research, ITMO University, St. Petersburg 197101, Russia
Publisher
MDPI
Link
https://www.mdpi.com/2673-4591/39/1/61/pdf
Reference17 articles.
1. Koshkareva, M. (2023, June 27). Available online: https://github.com/Mpkosh/Enhancement_of_Consumption_Forecasting.
2. Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects;Dumitrescu;Eur. J. Oper. Res.,2022
3. Karvana, K.G.M., Yazid, S., Syalim, A., and Mursanto, P. (2019, January 11). Customer Churn Analysis and Prediction Using Data Mining Models in Banking Industry. Proceedings of the International Workshop on Big Data and Information Security (IWBIS), Bali, Indonesia.
4. Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019;Magalingam;Comput. Sci. Rev.,2021
5. Fog computing architecture for personalized recommendation of banking products;Corchado;Expert Syst. Appl.,2020
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