Datasets:
ArXiv:
License:
| license: apache-2.0 | |
| task_categories: | |
| - other | |
| tags: | |
| - time-series | |
| - anomaly-detection | |
| # SMD+ Dataset | |
| SMD+ (Server Machine Dataset Plus) is a synthetic benchmark for Multivariate Time Series Anomaly Detection (MTSAD) featuring precise channel-wise annotations. It is designed to evaluate both time-wise detection and spatial anomaly localization capabilities. | |
| This dataset was introduced in the paper [POST: Prior-Observation Adversarial Learning of Spatio-Temporal Associations for Multivariate Time Series Anomaly Detection](https://huggingface.co/papers/2605.18128). | |
| - **Code:** [https://github.com/anocodetest1/POST](https://github.com/anocodetest1/POST) | |
| ## Sample Usage | |
| According to the official repository, you can evaluate a model on the SMD+ dataset using the following command: | |
| ```bash | |
| python main_channel.py --anomaly_ratio 0.5 --batch_size 64 --mode test --dataset SMD+ --data_path dataset/SMD+ --input_c 38 --output_c 38 | |
| ``` | |
| ## Citation | |
| Please consider citing the following work if you use this dataset: | |
| ```bibtex | |
| @misc{zhang2026postpriorobservationadversariallearning, | |
| title={POST: Prior-Observation Adversarial Learning of Spatio-Temporal Associations for Multivariate Time Series Anomaly Detection}, | |
| author={Suofei Zhang and Yaxuan Zheng and Haifeng Hu}, | |
| year={2026}, | |
| eprint={2605.18128}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.AI}, | |
| url={https://arxiv.org/abs/2605.18128}, | |
| } | |
| ``` |