An Explainable AI-based Intrusion Detection System for DNS over HTTPS (DoH) Attacks
paper.recording.mp4
You can install the package through pip:
pip install explainerdashboard
or conda-forge:
conda install -c conda-forge explainerdashboard
##The library includes:
- Shap values (i.e. what is the contributions of each feature to each individual prediction?)
- Permutation importances (how much does the model metric deteriorate when you shuffle a feature?)
- Partial dependence plots (how does the model prediction change when you vary a single feature?
- Shap interaction values (decompose the shap value into a direct effect an interaction effects)
- For Random Forests and xgboost models: visualisation of individual decision trees
- Plus for classifiers: precision plots, confusion matrix, ROC AUC plot, PR AUC plot, etc
You can store explainers to disk with explainer.dump("explainer.pkl")
and then run them from the command-line:
$ explainerdashboard run explainer.pkl