ClarifyShapConfig - Amazon SageMaker


The configuration for SHAP analysis using SageMaker Clarify Explainer.



The configuration for the SHAP baseline of the Kernal SHAP algorithm.

Type: ClarifyShapBaselineConfig object

Required: Yes


The number of samples to be used for analysis by the Kernal SHAP algorithm.


The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.

Type: Integer

Valid Range: Minimum value of 1.

Required: No


The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.

Type: Integer

Required: No


A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.

Type: ClarifyTextConfig object

Required: No


A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.

Type: Boolean

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: