CENTAURO: An Explainable AI Approach for Customer Loyalty Prediction in Retail Sector

Author:

Andresini GiuseppinaORCID,Appice AnnalisaORCID,Ardimento PasqualeORCID,Brunetta Andrea Antonio,Doronzo Antonio Giuseppe,Ieva Giuseppe,Luce Francesco,Malerba DonatoORCID,Pasquadibisceglie VincenzoORCID

Publisher

Springer Nature Switzerland

Reference10 articles.

1. Ahn, J., Hwang, J., Kim, D., Choi, H., Kang, S.: A survey on churn analysis in various business domains. IEEE Access 8, 220816–220839 (2020)

2. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);N Jha,2020

3. Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. In: Guyon, I., et al. (eds.) Advances in Neural Information Processing Systems, vol. 30. Curran Associates, Inc. (2017)

4. Martins, H.: Predicting user churn on streaming services using recurrent neural networks (2017)

5. Mena, C.G., De Caigny, A., Coussement, K., De Bock, K.W., Lessmann, S.: Churn prediction with sequential data and deep neural networks. a comparative analysis. arXiv preprint arXiv:1909.11114 (2019)

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