ClarifyShapConfig (AWS SDK for Java

java.lang.Object
- com.amazonaws.services.sagemaker.model.ClarifyShapConfig

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable
```
@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class ClarifyShapConfig
extends Object
implements Serializable, Cloneable, StructuredPojo
```
The configuration for SHAP analysis using SageMaker Clarify Explainer.

See Also:

AWS API Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

ClarifyShapConfig()

Constructors
Constructor and Description
`ClarifyShapConfig()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`ClarifyShapConfig`	`clone()`
`boolean`	`equals(Object obj)`
`Integer`	`getNumberOfSamples()` The number of samples to be used for analysis by the Kernal SHAP algorithm.
`Integer`	`getSeed()` The starting value used to initialize the random number generator in the explainer.
`ClarifyShapBaselineConfig`	`getShapBaselineConfig()` The configuration for the SHAP baseline of the Kernal SHAP algorithm.
`ClarifyTextConfig`	`getTextConfig()` A parameter that indicates if text features are treated as text and explanations are provided for individual units of text.
`Boolean`	`getUseLogit()` A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions.
`int`	`hashCode()`
`Boolean`	`isUseLogit()` A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions.
`void`	`marshall(ProtocolMarshaller protocolMarshaller)` Marshalls this structured data using the given `ProtocolMarshaller`.
`void`	`setNumberOfSamples(Integer numberOfSamples)` The number of samples to be used for analysis by the Kernal SHAP algorithm.
`void`	`setSeed(Integer seed)` The starting value used to initialize the random number generator in the explainer.
`void`	`setShapBaselineConfig(ClarifyShapBaselineConfig shapBaselineConfig)` The configuration for the SHAP baseline of the Kernal SHAP algorithm.
`void`	`setTextConfig(ClarifyTextConfig textConfig)` A parameter that indicates if text features are treated as text and explanations are provided for individual units of text.
`void`	`setUseLogit(Boolean useLogit)` A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions.
`String`	`toString()` Returns a string representation of this object.
`ClarifyShapConfig`	`withNumberOfSamples(Integer numberOfSamples)` The number of samples to be used for analysis by the Kernal SHAP algorithm.
`ClarifyShapConfig`	`withSeed(Integer seed)` The starting value used to initialize the random number generator in the explainer.
`ClarifyShapConfig`	`withShapBaselineConfig(ClarifyShapBaselineConfig shapBaselineConfig)` The configuration for the SHAP baseline of the Kernal SHAP algorithm.
`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`	`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 inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - ClarifyShapConfig
```
public ClarifyShapConfig()
```
- Method Detail
  - setShapBaselineConfig
```
public void setShapBaselineConfig(ClarifyShapBaselineConfig shapBaselineConfig)
```
    The configuration for the SHAP baseline of the Kernal SHAP algorithm.
    
    Parameters:
    
    shapBaselineConfig - The configuration for the SHAP baseline of the Kernal SHAP algorithm.
  - getShapBaselineConfig
```
public ClarifyShapBaselineConfig getShapBaselineConfig()
```
    The configuration for the SHAP baseline of the Kernal SHAP algorithm.
    
    Returns:
    
    The configuration for the SHAP baseline of the Kernal SHAP algorithm.
  - withShapBaselineConfig
```
public ClarifyShapConfig withShapBaselineConfig(ClarifyShapBaselineConfig shapBaselineConfig)
```
    The configuration for the SHAP baseline of the Kernal SHAP algorithm.
    
    Parameters:
    
    shapBaselineConfig - The configuration for the SHAP baseline of the Kernal SHAP algorithm.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setNumberOfSamples
```
public void setNumberOfSamples(Integer numberOfSamples)
```
    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.
    
    Parameters:
    
    numberOfSamples - 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.
  - getNumberOfSamples
```
public Integer 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.
    
    Returns:
    
    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.
  - withNumberOfSamples
```
public ClarifyShapConfig withNumberOfSamples(Integer numberOfSamples)
```
    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.
    
    Parameters:
    
    numberOfSamples - 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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setUseLogit
```
public void setUseLogit(Boolean useLogit)
```
    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.
    
    Parameters:
    
    useLogit - 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.
  - getUseLogit
```
public Boolean 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.
    
    Returns:
    
    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.
  - withUseLogit
```
public 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. Defaults to false.
    
    Parameters:
    
    useLogit - 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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - isUseLogit
```
public Boolean isUseLogit()
```
    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.
    
    Returns:
    
    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.
  - setSeed
```
public void setSeed(Integer seed)
```
    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.
    
    Parameters:
    
    seed - 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.
  - getSeed
```
public Integer 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.
    
    Returns:
    
    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.
  - withSeed
```
public ClarifyShapConfig withSeed(Integer seed)
```
    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.
    
    Parameters:
    
    seed - 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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTextConfig
```
public void setTextConfig(ClarifyTextConfig textConfig)
```
    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.
    
    Parameters:
    
    textConfig - 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.
  - getTextConfig
```
public ClarifyTextConfig 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.
    
    Returns:
    
    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.
  - withTextConfig
```
public ClarifyShapConfig withTextConfig(ClarifyTextConfig textConfig)
```
    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.
    
    Parameters:
    
    textConfig - 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.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public ClarifyShapConfig clone()
```
    Overrides:
    
    clone in class Object
  - marshall
```
public void marshall(ProtocolMarshaller protocolMarshaller)
```
    Description copied from interface: StructuredPojo
    
    Marshalls this structured data using the given ProtocolMarshaller.
    
    Specified by:
    
    marshall in interface StructuredPojo
    
    Parameters:
    
    protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.

AWS SDK for Java 1.x API Reference - 1.12.772

Class ClarifyShapConfig

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

ClarifyShapConfig

Method Detail

setShapBaselineConfig

getShapBaselineConfig

withShapBaselineConfig

setNumberOfSamples

getNumberOfSamples

withNumberOfSamples

setUseLogit

getUseLogit

withUseLogit

isUseLogit

setSeed

getSeed

withSeed

setTextConfig

getTextConfig

withTextConfig

toString

equals

hashCode

clone

marshall