Developing an Interpretable Machine Learning Model for Divorce Prediction

Author:

Satu Md. ShahriareORCID,Riyad Md. Mahmudul HasanORCID,Rony Mohammad Abu TareqORCID

Publisher

Springer Nature Singapore

Reference23 articles.

1. Ahmad S, Rosni RSAM (2019) Robust logistic regression in application to divorce data. In: Kor LK, Ahmad AR, Idrus Z, Mansor KA (eds) Proceedings of the third international conference on computing, mathematics and statistics (iCMS2017). Springer, Singapore, pp 421–427. https://doi.org/10.1007/978-981-13-7279-7_52

2. Akter T, Ali MH, Satu M, Khan M, Mahmud M et al (2021) Towards autism subtype detection through identification of discriminatory factors using machine learning. In: International conference on brain informatics. Springer, pp 401–410

3. Akter T, Khan MI, Ali MH, Satu MS, Uddin MJ, Moni MA (2021) Improved machine learning based classification model for early autism detection. In: 2021 2nd international conference on robotics, electrical and signal processing techniques (ICREST). IEEE, pp 742–747

4. Arpino B, Le Moglie M, Mencarin L (2018) Machine-learning techniques for family demography: an application of random forests to the analysis of divorce determinants in Germany. Universitat Pompeu Fabra (Barcelona), Research and Expertise Centre for Survey Methodology. Available at: https://www.upf.edu/documents/3966940/6839730/WP56.pdf/0aeb687a-38aa-bb04-4ba8-8813e9508148. Accessed 3 Apr 2020

5. Ashrafujjaman Tutul M, Hasan MM, Mondol SK, Hossain M, Al Marouf A (2021) Divorce prediction using machine learning methods-Bangladesh perspective. In: 2021 12th international conference on computing communication and networking technologies (ICCCNT), July 2021, pp 1–5. https://doi.org/10.1109/ICCCNT51525.2021.9579949

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