Amazon SageMaker Autopilot, which makes it easy to create highly accurate machine learning models, now provides a model explainability report generated by Amazon SageMaker Clarify, making it easier to understand and explain how the models you create with SageMaker Autopilot make predictions. Explainability reports include feature importance values so you can understand how each attribute in your training data contributes to the predicted result as a percentage. The higher the percentage, the more strongly that feature impacts your model’s predictions. You can download the explainability report as a human readable file, view model properties including feature importance in Amazon SageMaker Studio, or access feature importance using the SageMaker Autopilot APIs.
Source:: Amazon AWS