Outlier Detection for Time Series with Recurrent Autoencoder Ensembles

This is a TensorFlow implementation of Outlier Detection for Time Series with Recurrent Autoencoder Ensembles in the following paper: Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Outlier Detection for Time Series with Recurrent Autoencoder Ensembles, IJCAI 2019.

Requirements

• Python 3.x
• Numpy
• Pandas
• TensorFlow
• Scikit-learn

Dataset

We use two dataset NAB and ECG that is a public dataset. You can follow the links in the paper to download the dataset.

Model

We propose two model IF and SF

IF

SF

Citation

If you find this repository, e.g., the code and the datasets, useful in your research, please cite the following paper:

@inproceedings{tungbcc19,
  title={Outlier Detection for Time Series with Recurrent Autoencoder Ensembles},
  author={Kieu, Tung and Yang, Bin and Guo, Chenjuan and S. Jensen, Christian},
  booktitle={International Joint Conference on Artificial Intelligence (IJCAI '19)},
  year={2019}
}