Interface CfnEndpointConfig.ClarifyShapConfigProperty
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnEndpointConfig.ClarifyShapConfigProperty.Jsii$Proxy
- Enclosing class:
CfnEndpointConfig
@Stability(Stable)
public static interface CfnEndpointConfig.ClarifyShapConfigProperty
extends software.amazon.jsii.JsiiSerializable
The configuration for SHAP analysis using SageMaker Clarify Explainer.
Example:
// The code below shows an example of how to instantiate this type. // The values are placeholders you should change. import software.amazon.awscdk.services.sagemaker.*; ClarifyShapConfigProperty clarifyShapConfigProperty = ClarifyShapConfigProperty.builder() .shapBaselineConfig(ClarifyShapBaselineConfigProperty.builder() .mimeType("mimeType") .shapBaseline("shapBaseline") .shapBaselineUri("shapBaselineUri") .build()) // the properties below are optional .numberOfSamples(123) .seed(123) .textConfig(ClarifyTextConfigProperty.builder() .granularity("granularity") .language("language") .build()) .useLogit(false) .build();
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Nested Class Summary
Nested ClassesModifier and TypeInterfaceDescriptionstatic final class
A builder forCfnEndpointConfig.ClarifyShapConfigProperty
static final class
An implementation forCfnEndpointConfig.ClarifyShapConfigProperty
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Method Summary
Modifier and TypeMethodDescriptionbuilder()
default Number
The number of samples to be used for analysis by the Kernal SHAP algorithm.default Number
getSeed()
The starting value used to initialize the random number generator in the explainer.The configuration for the SHAP baseline of the Kernal SHAP algorithm.default Object
A parameter that indicates if text features are treated as text and explanations are provided for individual units of text.default Object
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
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Method Details
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getShapBaselineConfig
The configuration for the SHAP baseline of the Kernal SHAP algorithm.- See Also:
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getNumberOfSamples
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 .
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getSeed
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.
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getTextConfig
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.
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getUseLogit
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.
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builder
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