Uses of Class
com.amazonaws.services.sagemaker.model.ClarifyShapConfig

Packages that use ClarifyShapConfig

Package	Description
com.amazonaws.services.sagemaker.model

Uses of ClarifyShapConfig in com.amazonaws.services.sagemaker.model

Methods in com.amazonaws.services.sagemaker.model that return ClarifyShapConfig

Modifier and Type	Method and Description
ClarifyShapConfig	ClarifyShapConfig.clone()
ClarifyShapConfig	ClarifyExplainerConfig.getShapConfig() The configuration for SHAP analysis.
ClarifyShapConfig	ClarifyShapConfig.withNumberOfSamples(Integer numberOfSamples) The number of samples to be used for analysis by the Kernal SHAP algorithm.
ClarifyShapConfig	ClarifyShapConfig.withSeed(Integer seed) The starting value used to initialize the random number generator in the explainer.
ClarifyShapConfig	ClarifyShapConfig.withShapBaselineConfig(ClarifyShapBaselineConfig shapBaselineConfig) The configuration for the SHAP baseline of the Kernal SHAP algorithm.
ClarifyShapConfig	ClarifyShapConfig.withTextConfig(ClarifyTextConfig textConfig) A parameter that indicates if text features are treated as text and explanations are provided for individual units of text.
ClarifyShapConfig	ClarifyShapConfig.withUseLogit(Boolean useLogit) A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions.

Methods in com.amazonaws.services.sagemaker.model with parameters of type ClarifyShapConfig

Modifier and Type	Method and Description
void	ClarifyExplainerConfig.setShapConfig(ClarifyShapConfig shapConfig) The configuration for SHAP analysis.
ClarifyExplainerConfig	ClarifyExplainerConfig.withShapConfig(ClarifyShapConfig shapConfig) The configuration for SHAP analysis.