The aim of this repository is to test how USAD (UnSupervised Anomaly Detection on multivariate time series) behaves on UCR Time Series Anomaly Archive dataset.
The model was created based on this paper: Audibert et al. USAD : UnSupervised Anomaly Detection on multivariate time series. 2020 and its implementation by Francesco Galati - Github .
Full implementation can be found in src/model.py.
Examples on how the model behaves on different dataset can be found in: finloop/usad-torchlightning.
The data comes from UCR Time Series Anomaly Archive . Download link: https://www.cs.ucr.edu/~eamonn/time_series_data_2018/UCR_TimeSeriesAnomalyDatasets2021.zip
To run this put contents of ZIPFILE/UCR_TimeSeriesAnomalyDatasets2021/FilesAreInHere/UCR_Anomaly_FullData to datasets/data
.
Install requirements:
- pytorch
- pytorch-lightning
- jupyterlab
To run open and run: notebooks/UCR_Anomaly.ipynb.
The model (for now) was tested on dataset 003. This is how it looks:
The model seems to perform poorly. It is unable to find the desired anomaly(
the bigger the reconstruction error - the
stronger the anomaly). The biggest reconstruction error is not near the red
area.
