Interface ModelSummary.Builder
- All Superinterfaces:
- Buildable,- CopyableBuilder<ModelSummary.Builder,,- ModelSummary> - SdkBuilder<ModelSummary.Builder,,- ModelSummary> - SdkPojo
- Enclosing class:
- ModelSummary
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Method SummaryModifier and TypeMethodDescriptionactiveModelVersion(Long activeModelVersion) The model version that the inference scheduler uses to run an inference execution.activeModelVersionArn(String activeModelVersionArn) The Amazon Resource Name (ARN) of the model version that is set as active.The time at which the specific model was created.datasetArn(String datasetArn) The Amazon Resource Name (ARN) of the dataset used to create the model.datasetName(String datasetName) The name of the dataset being used for the machine learning model.latestScheduledRetrainingModelVersion(Long latestScheduledRetrainingModelVersion) Indicates the most recent model version that was generated by retraining.latestScheduledRetrainingStartTime(Instant latestScheduledRetrainingStartTime) Indicates the start time of the most recent scheduled retraining run.latestScheduledRetrainingStatus(String latestScheduledRetrainingStatus) Indicates the status of the most recent scheduled retraining run.latestScheduledRetrainingStatus(ModelVersionStatus latestScheduledRetrainingStatus) Indicates the status of the most recent scheduled retraining run.The Amazon Resource Name (ARN) of the machine learning model.default ModelSummary.BuildermodelDiagnosticsOutputConfiguration(Consumer<ModelDiagnosticsOutputConfiguration.Builder> modelDiagnosticsOutputConfiguration) Sets the value of the ModelDiagnosticsOutputConfiguration property for this object.modelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration) Sets the value of the ModelDiagnosticsOutputConfiguration property for this object.The name of the machine learning model.modelQuality(String modelQuality) Provides a quality assessment for a model that uses labels.modelQuality(ModelQuality modelQuality) Provides a quality assessment for a model that uses labels.nextScheduledRetrainingStartDate(Instant nextScheduledRetrainingStartDate) Indicates the date that the next scheduled retraining run will start on.retrainingSchedulerStatus(String retrainingSchedulerStatus) Indicates the status of the retraining scheduler.retrainingSchedulerStatus(RetrainingSchedulerStatus retrainingSchedulerStatus) Indicates the status of the retraining scheduler.Indicates the status of the machine learning model.status(ModelStatus status) Indicates the status of the machine learning model.Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuildercopyMethods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilderapplyMutation, buildMethods inherited from interface software.amazon.awssdk.core.SdkPojoequalsBySdkFields, sdkFieldNameToField, sdkFields
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Method Details- 
modelNameThe name of the machine learning model. - Parameters:
- modelName- The name of the machine learning model.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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modelArnThe Amazon Resource Name (ARN) of the machine learning model. - Parameters:
- modelArn- The Amazon Resource Name (ARN) of the machine learning model.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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datasetNameThe name of the dataset being used for the machine learning model. - Parameters:
- datasetName- The name of the dataset being used for the machine learning model.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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datasetArnThe Amazon Resource Name (ARN) of the dataset used to create the model. - Parameters:
- datasetArn- The Amazon Resource Name (ARN) of the dataset used to create the model.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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statusIndicates the status of the machine learning model. - Parameters:
- status- Indicates the status of the machine learning model.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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statusIndicates the status of the machine learning model. - Parameters:
- status- Indicates the status of the machine learning model.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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createdAtThe time at which the specific model was created. - Parameters:
- createdAt- The time at which the specific model was created.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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activeModelVersionThe model version that the inference scheduler uses to run an inference execution. - Parameters:
- activeModelVersion- The model version that the inference scheduler uses to run an inference execution.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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activeModelVersionArnThe Amazon Resource Name (ARN) of the model version that is set as active. The active model version is the model version that the inference scheduler uses to run an inference execution. - Parameters:
- activeModelVersionArn- The Amazon Resource Name (ARN) of the model version that is set as active. The active model version is the model version that the inference scheduler uses to run an inference execution.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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latestScheduledRetrainingStatusIndicates the status of the most recent scheduled retraining run. - Parameters:
- latestScheduledRetrainingStatus- Indicates the status of the most recent scheduled retraining run.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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latestScheduledRetrainingStatusModelSummary.Builder latestScheduledRetrainingStatus(ModelVersionStatus latestScheduledRetrainingStatus) Indicates the status of the most recent scheduled retraining run. - Parameters:
- latestScheduledRetrainingStatus- Indicates the status of the most recent scheduled retraining run.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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latestScheduledRetrainingModelVersionModelSummary.Builder latestScheduledRetrainingModelVersion(Long latestScheduledRetrainingModelVersion) Indicates the most recent model version that was generated by retraining. - Parameters:
- latestScheduledRetrainingModelVersion- Indicates the most recent model version that was generated by retraining.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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latestScheduledRetrainingStartTimeIndicates the start time of the most recent scheduled retraining run. - Parameters:
- latestScheduledRetrainingStartTime- Indicates the start time of the most recent scheduled retraining run.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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nextScheduledRetrainingStartDateIndicates the date that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day. - Parameters:
- nextScheduledRetrainingStartDate- Indicates the date that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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retrainingSchedulerStatusIndicates the status of the retraining scheduler. - Parameters:
- retrainingSchedulerStatus- Indicates the status of the retraining scheduler.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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retrainingSchedulerStatusIndicates the status of the retraining scheduler. - Parameters:
- retrainingSchedulerStatus- Indicates the status of the retraining scheduler.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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modelDiagnosticsOutputConfigurationModelSummary.Builder modelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration) Sets the value of the ModelDiagnosticsOutputConfiguration property for this object.- Parameters:
- modelDiagnosticsOutputConfiguration- The new value for the ModelDiagnosticsOutputConfiguration property for this object.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
 
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modelDiagnosticsOutputConfigurationdefault ModelSummary.Builder modelDiagnosticsOutputConfiguration(Consumer<ModelDiagnosticsOutputConfiguration.Builder> modelDiagnosticsOutputConfiguration) Sets the value of the ModelDiagnosticsOutputConfiguration property for this object. This is a convenience method that creates an instance of theModelDiagnosticsOutputConfiguration.Builderavoiding the need to create one manually viaModelDiagnosticsOutputConfiguration.builder().When the Consumercompletes,SdkBuilder.build()is called immediately and its result is passed tomodelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration).- Parameters:
- modelDiagnosticsOutputConfiguration- a consumer that will call methods on- ModelDiagnosticsOutputConfiguration.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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modelQualityProvides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value isQUALITY_THRESHOLD_MET.If the model is unlabeled, the model quality can't be assessed and the value of ModelQualityisCANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.For information about using labels with your models, see Understanding labeling. For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment. - Parameters:
- modelQuality- Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is- POOR_QUALITY_DETECTED. Otherwise, the value is- QUALITY_THRESHOLD_MET.- If the model is unlabeled, the model quality can't be assessed and the value of - ModelQualityis- CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.- For information about using labels with your models, see Understanding labeling. - For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment. 
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
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modelQualityProvides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value isQUALITY_THRESHOLD_MET.If the model is unlabeled, the model quality can't be assessed and the value of ModelQualityisCANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.For information about using labels with your models, see Understanding labeling. For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment. - Parameters:
- modelQuality- Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is- POOR_QUALITY_DETECTED. Otherwise, the value is- QUALITY_THRESHOLD_MET.- If the model is unlabeled, the model quality can't be assessed and the value of - ModelQualityis- CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.- For information about using labels with your models, see Understanding labeling. - For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment. 
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
 
 
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