DWS-MMD-Streamify-Time-Series-Anomaly-Detection-Methods

Instructions for 157.ipynb (HBOS, POLY, CNN)

Tested using conda 23.7.2 on Ubuntu 22.04.3 LTS

conda env create -f environment_157.yml

conda activate TSB

cd TSB-UAD_157

pip install .

then run the notebook either on Jupyter or VSCode with the appropriate extension.

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
.idea		.idea
TSB-UAD_157		TSB-UAD_157
generated_data		generated_data
original_data		original_data
results		results
utils		utils
.gitignore		.gitignore
157.html		157.html
157.ipynb		157.ipynb
157.pdf		157.pdf
Project.pdf		Project.pdf
README.md		README.md
Report.pdf		Report.pdf
data_generation.ipynb		data_generation.ipynb
environment_157.yml		environment_157.yml
iforest.html		iforest.html
iforest.ipynb		iforest.ipynb
iforest.pdf		iforest.pdf
iforest_naive.py		iforest_naive.py
iforest_optimal.py		iforest_optimal.py
lstm_supervised.html		lstm_supervised.html
lstm_supervised.ipynb		lstm_supervised.ipynb
lstm_supervised.pdf		lstm_supervised.pdf
metrics.py		metrics.py
results_157.ods		results_157.ods
slidingWindows.py		slidingWindows.py