Prediction of rare events in the operation of household equipment using co-evolving time series

• URL: http://arxiv.org/abs/2312.09410v1
• Date: Fri, 15 Dec 2023 00:21:00 GMT
• Title: Prediction of rare events in the operation of household equipment using co-evolving time series
• Authors: Hadia Mecheri, Islam Benamirouche, Feriel Fass, Djemel Ziou, Nassima Kadri
• Abstract summary: Our approach involves a weighted autologistic regression model, where we leverage the temporal behavior of the data to enhance predictive capabilities. Evaluation on synthetic and real-world datasets confirms that our approach outperform state-of-the-art of predicting home equipment failure methods.
• Score: 1.1249583407496218
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this study, we propose an approach for predicting rare events by exploiting time series in coevolution. Our approach involves a weighted autologistic regression model, where we leverage the temporal behavior of the data to enhance predictive capabilities. By addressing the issue of imbalanced datasets, we establish constraints leading to weight estimation and to improved performance. Evaluation on synthetic and real-world datasets confirms that our approach outperform state-of-the-art of predicting home equipment failure methods.

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