README.md
setup.cfg
setup.py
explainx/__init__.py
explainx/explain.py
explainx/pytest.py
explainx/run_only_first_time.py
explainx.egg-info/PKG-INFO
explainx.egg-info/SOURCES.txt
explainx.egg-info/dependency_links.txt
explainx.egg-info/requires.txt
explainx.egg-info/top_level.txt
explainx/datasets/heloc_dataset.csv
explainx/lib/PDASH.py
explainx/lib/PDASH_utils.py
explainx/lib/__init__.py
explainx/lib/app.py
explainx/lib/calculate_metrics.py
explainx/lib/calculate_shap.py
explainx/lib/dashboard.py
explainx/lib/data_for_shap_graphs.py
explainx/lib/die.py
explainx/lib/draw_dataframe.py
explainx/lib/encode_decode_cat_col.py
explainx/lib/feature_impact.py
explainx/lib/feature_importance.py
explainx/lib/imports.py
explainx/lib/index.py
explainx/lib/insight_classification.py
explainx/lib/insight_regression.py
explainx/lib/insights.py
explainx/lib/performance_metrics.py
explainx/lib/plotly_css.py
explainx/lib/plotly_graphs.py
explainx/lib/protodash.py
explainx/lib/rescale_numeric_feature.py
explainx/lib/shap_pdp.py
explainx/lib/summary_plot.py
explainx/lib/what_if.py
explainx/lib/xai.png
explainx/lib/apps/distribution.py
explainx/lib/apps/feature_interaction.py
explainx/lib/apps/german_train.csv
explainx/lib/apps/global_explanation.py
explainx/lib/apps/local_explanation.py
explainx/tutorials/1. Xgboost Model on Boston Dataset.ipynb
explainx/tutorials/10.  Gradient Boosting Regressor on Boston Dataset.ipynb
explainx/tutorials/2. Xgboost Model on Heloc Dataset.ipynb
explainx/tutorials/3. Catboost Model on Boston Dataset.ipynb
explainx/tutorials/4. Randomforest Model on iris Dataset.ipynb
explainx/tutorials/5 Support Vector Classifier on iris Dataset.ipynb
explainx/tutorials/6. KNeighborsClassifier on iris Dataset.ipynb
explainx/tutorials/7. Logistic Regression on iris dataset.ipynb
explainx/tutorials/8. DecisionTreeClassifier on iris Dataset.ipynb
explainx/tutorials/9.  Neural Network Classifier on iris Dataset.ipynb
explainx/tutorials/tutorials.txt