mlflow--mlflow/examples/shap

SHAP Examples

Examples demonstrating use of the mlflow.shap APIs for model explainability.

File	Task	Description
regression.py	Regression	Log explanations for a LinearRegression model
binary_classification.py	Binary classification	Log explanations for a binary RandomForestClassifier model
multiclass_classification.py	Multiclass classification	Log explanations for a multiclass RandomForestClassifier model

Prerequisites

Run the following command to install required packages:

pip install mlflow scikit-learn shap matplotlib

How to run the scripts

python <script_name>

How to view the logged explanations:

• Run mlflow server to launch the MLflow UI.
• Open http://127.0.0.1:5000 on your browser.
• Click the latest run in the runs table.
• Scroll down to the artifact viewer.
• Open a folder named model_explanations_shap.