@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class SolutionConfig extends Object implements Serializable, Cloneable, StructuredPojo
Describes the configuration properties for the solution.
Constructor and Description |
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SolutionConfig() |
Modifier and Type | Method and Description |
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SolutionConfig |
addAlgorithmHyperParametersEntry(String key,
String value)
Add a single AlgorithmHyperParameters entry
|
SolutionConfig |
addFeatureTransformationParametersEntry(String key,
String value)
Add a single FeatureTransformationParameters entry
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SolutionConfig |
clearAlgorithmHyperParametersEntries()
Removes all the entries added into AlgorithmHyperParameters.
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SolutionConfig |
clearFeatureTransformationParametersEntries()
Removes all the entries added into FeatureTransformationParameters.
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SolutionConfig |
clone() |
boolean |
equals(Object obj) |
Map<String,String> |
getAlgorithmHyperParameters()
Lists the algorithm hyperparameters and their values.
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AutoMLConfig |
getAutoMLConfig()
The AutoMLConfig object
containing a list of recipes to search when AutoML is performed.
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AutoTrainingConfig |
getAutoTrainingConfig()
Specifies the automatic training configuration to use.
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String |
getEventValueThreshold()
Only events with a value greater than or equal to this threshold are used for training a model.
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Map<String,String> |
getFeatureTransformationParameters()
Lists the feature transformation parameters.
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HPOConfig |
getHpoConfig()
Describes the properties for hyperparameter optimization (HPO).
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OptimizationObjective |
getOptimizationObjective()
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue.
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TrainingDataConfig |
getTrainingDataConfig()
Specifies the training data configuration to use when creating a custom solution version (trained model).
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int |
hashCode() |
void |
marshall(ProtocolMarshaller protocolMarshaller)
Marshalls this structured data using the given
ProtocolMarshaller . |
void |
setAlgorithmHyperParameters(Map<String,String> algorithmHyperParameters)
Lists the algorithm hyperparameters and their values.
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void |
setAutoMLConfig(AutoMLConfig autoMLConfig)
The AutoMLConfig object
containing a list of recipes to search when AutoML is performed.
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void |
setAutoTrainingConfig(AutoTrainingConfig autoTrainingConfig)
Specifies the automatic training configuration to use.
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void |
setEventValueThreshold(String eventValueThreshold)
Only events with a value greater than or equal to this threshold are used for training a model.
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void |
setFeatureTransformationParameters(Map<String,String> featureTransformationParameters)
Lists the feature transformation parameters.
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void |
setHpoConfig(HPOConfig hpoConfig)
Describes the properties for hyperparameter optimization (HPO).
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void |
setOptimizationObjective(OptimizationObjective optimizationObjective)
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue.
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void |
setTrainingDataConfig(TrainingDataConfig trainingDataConfig)
Specifies the training data configuration to use when creating a custom solution version (trained model).
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String |
toString()
Returns a string representation of this object.
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SolutionConfig |
withAlgorithmHyperParameters(Map<String,String> algorithmHyperParameters)
Lists the algorithm hyperparameters and their values.
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SolutionConfig |
withAutoMLConfig(AutoMLConfig autoMLConfig)
The AutoMLConfig object
containing a list of recipes to search when AutoML is performed.
|
SolutionConfig |
withAutoTrainingConfig(AutoTrainingConfig autoTrainingConfig)
Specifies the automatic training configuration to use.
|
SolutionConfig |
withEventValueThreshold(String eventValueThreshold)
Only events with a value greater than or equal to this threshold are used for training a model.
|
SolutionConfig |
withFeatureTransformationParameters(Map<String,String> featureTransformationParameters)
Lists the feature transformation parameters.
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SolutionConfig |
withHpoConfig(HPOConfig hpoConfig)
Describes the properties for hyperparameter optimization (HPO).
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SolutionConfig |
withOptimizationObjective(OptimizationObjective optimizationObjective)
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue.
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SolutionConfig |
withTrainingDataConfig(TrainingDataConfig trainingDataConfig)
Specifies the training data configuration to use when creating a custom solution version (trained model).
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public void setEventValueThreshold(String eventValueThreshold)
Only events with a value greater than or equal to this threshold are used for training a model.
eventValueThreshold
- Only events with a value greater than or equal to this threshold are used for training a model.public String getEventValueThreshold()
Only events with a value greater than or equal to this threshold are used for training a model.
public SolutionConfig withEventValueThreshold(String eventValueThreshold)
Only events with a value greater than or equal to this threshold are used for training a model.
eventValueThreshold
- Only events with a value greater than or equal to this threshold are used for training a model.public void setHpoConfig(HPOConfig hpoConfig)
Describes the properties for hyperparameter optimization (HPO).
hpoConfig
- Describes the properties for hyperparameter optimization (HPO).public HPOConfig getHpoConfig()
Describes the properties for hyperparameter optimization (HPO).
public SolutionConfig withHpoConfig(HPOConfig hpoConfig)
Describes the properties for hyperparameter optimization (HPO).
hpoConfig
- Describes the properties for hyperparameter optimization (HPO).public Map<String,String> getAlgorithmHyperParameters()
Lists the algorithm hyperparameters and their values.
public void setAlgorithmHyperParameters(Map<String,String> algorithmHyperParameters)
Lists the algorithm hyperparameters and their values.
algorithmHyperParameters
- Lists the algorithm hyperparameters and their values.public SolutionConfig withAlgorithmHyperParameters(Map<String,String> algorithmHyperParameters)
Lists the algorithm hyperparameters and their values.
algorithmHyperParameters
- Lists the algorithm hyperparameters and their values.public SolutionConfig addAlgorithmHyperParametersEntry(String key, String value)
public SolutionConfig clearAlgorithmHyperParametersEntries()
public Map<String,String> getFeatureTransformationParameters()
Lists the feature transformation parameters.
public void setFeatureTransformationParameters(Map<String,String> featureTransformationParameters)
Lists the feature transformation parameters.
featureTransformationParameters
- Lists the feature transformation parameters.public SolutionConfig withFeatureTransformationParameters(Map<String,String> featureTransformationParameters)
Lists the feature transformation parameters.
featureTransformationParameters
- Lists the feature transformation parameters.public SolutionConfig addFeatureTransformationParametersEntry(String key, String value)
public SolutionConfig clearFeatureTransformationParametersEntries()
public void setAutoMLConfig(AutoMLConfig autoMLConfig)
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
autoMLConfig
- The AutoMLConfig
object containing a list of recipes to search when AutoML is performed.public AutoMLConfig getAutoMLConfig()
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
public SolutionConfig withAutoMLConfig(AutoMLConfig autoMLConfig)
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
autoMLConfig
- The AutoMLConfig
object containing a list of recipes to search when AutoML is performed.public void setOptimizationObjective(OptimizationObjective optimizationObjective)
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.
optimizationObjective
- Describes the additional objective for the solution, such as maximizing streaming minutes or increasing
revenue. For more information see Optimizing
a solution.public OptimizationObjective getOptimizationObjective()
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.
public SolutionConfig withOptimizationObjective(OptimizationObjective optimizationObjective)
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.
optimizationObjective
- Describes the additional objective for the solution, such as maximizing streaming minutes or increasing
revenue. For more information see Optimizing
a solution.public void setTrainingDataConfig(TrainingDataConfig trainingDataConfig)
Specifies the training data configuration to use when creating a custom solution version (trained model).
trainingDataConfig
- Specifies the training data configuration to use when creating a custom solution version (trained model).public TrainingDataConfig getTrainingDataConfig()
Specifies the training data configuration to use when creating a custom solution version (trained model).
public SolutionConfig withTrainingDataConfig(TrainingDataConfig trainingDataConfig)
Specifies the training data configuration to use when creating a custom solution version (trained model).
trainingDataConfig
- Specifies the training data configuration to use when creating a custom solution version (trained model).public void setAutoTrainingConfig(AutoTrainingConfig autoTrainingConfig)
Specifies the automatic training configuration to use.
autoTrainingConfig
- Specifies the automatic training configuration to use.public AutoTrainingConfig getAutoTrainingConfig()
Specifies the automatic training configuration to use.
public SolutionConfig withAutoTrainingConfig(AutoTrainingConfig autoTrainingConfig)
Specifies the automatic training configuration to use.
autoTrainingConfig
- Specifies the automatic training configuration to use.public String toString()
toString
in class Object
Object.toString()
public SolutionConfig clone()
public void marshall(ProtocolMarshaller protocolMarshaller)
StructuredPojo
ProtocolMarshaller
.marshall
in interface StructuredPojo
protocolMarshaller
- Implementation of ProtocolMarshaller
used to marshall this object's data.