Outlier Detection for Time Series with Recurrent Autoencoder Ensembles
May 28, 2019 ยท View on GitHub
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}
}