Skip to content

using Azure ML to explain model predictions and provide feature importances at inference time

License

Notifications You must be signed in to change notification settings

microsoft-partner-solutions-ai/model-explainability

Repository files navigation

Model Explainability

Use model interprebility in Azure ML to explain model predictions and provide feature importances at inference time.

  • create_explanations generate and pickle the explainer object for the best model of an AutoML run.
  • deploy_explanations deploy a web service with the model explanations and model predictions. Also generate the scoring script that goes with the deployment.

About

using Azure ML to explain model predictions and provide feature importances at inference time

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published