Deep Learning for Time Series Classification: a brief overview

Source: Deep Learning on Medium

Conclusion

In this post, I presented a brief introduction on how to adapt deep learning models for time series classification. I hope you managed to have an overview of CNNs for time series classification and if you are interested in learning the details of these models I recommend reading the relevant papers as well as checking out a recent study group on the fast.ai forums.

References

[1] Dau, H. A., Bagnall, A., Kamgar, K., Yeh, C. C. M., Zhu, Y., Gharghabi, S., … & Keogh, E. (2018). The UCR time series archive. arXiv preprint arXiv:1810.07758.

[2] Bagnall, A., Lines, J., Bostrom, A., Large, J., & Keogh, E. (2017). The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery, 31(3), 606–660.

[3] Lines, J., Taylor, S., & Bagnall, A. (2016, December). Hive-cote: The hierarchical vote collective of transformation-based ensembles for time series classification. In 2016 IEEE 16th international conference on data mining (ICDM) (pp. 1041–1046). IEEE.

[4] Wang, Z., Yan, W., & Oates, T. (2017, May). Time series classification from scratch with deep neural networks: A strong baseline. In 2017 international joint conference on neural networks (IJCNN) (pp. 1578–1585). IEEE.

[5] Ismail Fawaz, H., Forestier, G., Weber, J., Idoumghar, L., & Muller, P. A. (2019). Deep learning for time series classification: a review. Data Mining and Knowledge Discovery, 33(4), 917–963.

[6] Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems (pp. 1097–1105).

[7] Ismail Fawaz, H., Lucas, B., Forestier, G., Pelletier, C., Schmidt, D. F., Weber, J., … & Petitjean, F. (2019). InceptionTime: Finding AlexNet for Time Series Classification. arXiv preprint arXiv:1909.04939.

[8] Szegedy, C., Ioffe, S., Vanhoucke, V., & Alemi, A. A. (2017, February). Inception-v4, inception-resnet and the impact of residual connections on learning. In Thirty-First AAAI Conference on Artificial Intelligence.