Uncertain Time Series Classification

Uncertain Time Series Classification

Michael Franklin Mbouopda

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Doctoral Consortium. Pages 4903-4904. https://doi.org/10.24963/ijcai.2021/683

Time series analysis has gained a lot of interest during the last decade with diverse applications in a large range of domains such as medicine, physic, and industry. The field of time series classification has been particularly active recently with the development of more and more efficient methods. However, the existing methods assume that the input time series is free of uncertainty. However, there are applications in which uncertainty is so important that it can not be neglected. This project aims to build efficient, robust, and interpretable classification methods for uncertain time series.
Keywords:
Machine Learning: Time-series; Data Streams
Machine Learning: Classification
Machine Learning: Explainable/Interpretable Machine Learning