Class-wise confidence for debt prediction in real estate management: discussion and lessons learned from an application

Soundouss Messoudi, Sébastien Destercke, Sylvain Rousseau
Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications, PMLR 152:211-228, 2021.

Abstract

The prediction of tenants likely to fall into a debt situation is a key issue for social property owners in real estate. It is even more important for them to limit the number of people falsely predicted to be in debt to avoid incurring unnecessary costs (in time and money), for instance by sending agents to prevent the debt. In this paper, we adapt Mondrian conformal prediction to control the error rate of this class, while keeping a level of confidence chosen by the social property owner, or more generally by the user. We also test this small adaptation with different splitting strategies and discuss the obtained results, those later showing promising results, in the sense that they show that our approach can work, as well as pointing out and discussing difficulties, in the sense that conformal prediction fails on some settings of particular interest to the end-user.

Cite this Paper

BibTeX
@InProceedings{pmlr-v152-messoudi21a, title = {Class-wise confidence for debt prediction in real estate management: discussion and lessons learned from an application}, author = {Messoudi, Soundouss and Destercke, S\'{e}bastien and Rousseau, Sylvain}, booktitle = {Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications}, pages = {211--228}, year = {2021}, editor = {Carlsson, Lars and Luo, Zhiyuan and Cherubin, Giovanni and An Nguyen, Khuong}, volume = {152}, series = {Proceedings of Machine Learning Research}, month = {08--10 Sep}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v152/messoudi21a/messoudi21a.pdf}, url = {https://proceedings.mlr.press/v152/messoudi21a.html}, abstract = {The prediction of tenants likely to fall into a debt situation is a key issue for social property owners in real estate. It is even more important for them to limit the number of people falsely predicted to be in debt to avoid incurring unnecessary costs (in time and money), for instance by sending agents to prevent the debt. In this paper, we adapt Mondrian conformal prediction to control the error rate of this class, while keeping a level of confidence chosen by the social property owner, or more generally by the user. We also test this small adaptation with different splitting strategies and discuss the obtained results, those later showing promising results, in the sense that they show that our approach can work, as well as pointing out and discussing difficulties, in the sense that conformal prediction fails on some settings of particular interest to the end-user.} }
Endnote
%0 Conference Paper %T Class-wise confidence for debt prediction in real estate management: discussion and lessons learned from an application %A Soundouss Messoudi %A Sébastien Destercke %A Sylvain Rousseau %B Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications %C Proceedings of Machine Learning Research %D 2021 %E Lars Carlsson %E Zhiyuan Luo %E Giovanni Cherubin %E Khuong An Nguyen %F pmlr-v152-messoudi21a %I PMLR %P 211--228 %U https://proceedings.mlr.press/v152/messoudi21a.html %V 152 %X The prediction of tenants likely to fall into a debt situation is a key issue for social property owners in real estate. It is even more important for them to limit the number of people falsely predicted to be in debt to avoid incurring unnecessary costs (in time and money), for instance by sending agents to prevent the debt. In this paper, we adapt Mondrian conformal prediction to control the error rate of this class, while keeping a level of confidence chosen by the social property owner, or more generally by the user. We also test this small adaptation with different splitting strategies and discuss the obtained results, those later showing promising results, in the sense that they show that our approach can work, as well as pointing out and discussing difficulties, in the sense that conformal prediction fails on some settings of particular interest to the end-user.
APA
Messoudi, S., Destercke, S. & Rousseau, S.. (2021). Class-wise confidence for debt prediction in real estate management: discussion and lessons learned from an application. Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications, in Proceedings of Machine Learning Research 152:211-228 Available from https://proceedings.mlr.press/v152/messoudi21a.html.

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