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TracInAD

arXiv

Repository containing the code for the experiments of TracInAD : Measuring Influence for Anomaly Detection accepted in the proceedings of IJCNN 2022.

Data

To run experiments, datasets must be downloaded in folder data:

cd tracinad_wcci2022
bash ./data/data.sh

data.sh requires wget to be installed. For Mac user, replace with curl in data.sh.

Requirements

To run the experiments, use the requirements.txt file to install the dependencies. Using virtualenv:

cd TracInAD
virtualenv tracinad_env
source ./tracinad_env/bin/activate
pip install -r requirements.txt

Using conda:

cd TracInAD
conda create -n tracinad_env
conda activate tracinad_env
conda install --file requirements.txt

Experiments

To run experiments:

cd TracInAD
source ./tracinad_env/bin/activate
bash run.sh -d arrhythmia

For other datasets, replace arrhythmia by a dataset contained in [thyroid, arrhythmia, kdd, kddrev].

If you use this code, please cite us:

@inproceedings{Thimonier_2022,
   title={Trac{I}n{AD}: Measuring Influence for Anomaly Detection},
   url={http://dx.doi.org/10.1109/IJCNN55064.2022.9892058},
   DOI={10.1109/ijcnn55064.2022.9892058},
   booktitle={2022 International Joint Conference on Neural Networks (IJCNN)},
   publisher={IEEE},
   author={Thimonier, Hugo and Popineau, Fabrice and Rimmel, Arpad and Doan, Bich-Lien and Daniel, Fabrice},
   year={2022},
   month=jul }

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Repository containing the code for the experiments of TracInAD : Measuring Influence for Anomaly Detection accepted in the proceedings of IJCNN 2022.

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