Interface DescribeModelResponse.Builder
- All Superinterfaces:
AwsResponse.Builder
,Buildable
,CopyableBuilder<DescribeModelResponse.Builder,
,DescribeModelResponse> LookoutEquipmentResponse.Builder
,SdkBuilder<DescribeModelResponse.Builder,
,DescribeModelResponse> SdkPojo
,SdkResponse.Builder
- Enclosing class:
DescribeModelResponse
-
Method Summary
Modifier and TypeMethodDescriptionaccumulatedInferenceDataEndTime
(Instant accumulatedInferenceDataEndTime) Indicates the end time of the inference data that has been accumulated.accumulatedInferenceDataStartTime
(Instant accumulatedInferenceDataStartTime) Indicates the start time of the inference data that has been accumulated.activeModelVersion
(Long activeModelVersion) The name of the model version used by the inference schedular when running a scheduled inference execution.activeModelVersionArn
(String activeModelVersionArn) The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.Indicates the time and date at which the machine learning model was created.default DescribeModelResponse.Builder
dataPreProcessingConfiguration
(Consumer<DataPreProcessingConfiguration.Builder> dataPreProcessingConfiguration) The configuration is theTargetSamplingRate
, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment.dataPreProcessingConfiguration
(DataPreProcessingConfiguration dataPreProcessingConfiguration) The configuration is theTargetSamplingRate
, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment.datasetArn
(String datasetArn) The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.datasetName
(String datasetName) The name of the dataset being used by the machine learning being described.evaluationDataEndTime
(Instant evaluationDataEndTime) Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.evaluationDataStartTime
(Instant evaluationDataStartTime) Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.failedReason
(String failedReason) If the training of the machine learning model failed, this indicates the reason for that failure.importJobEndTime
(Instant importJobEndTime) The date and time when the import job was completed.importJobStartTime
(Instant importJobStartTime) The date and time when the import job was started.default DescribeModelResponse.Builder
labelsInputConfiguration
(Consumer<LabelsInputConfiguration.Builder> labelsInputConfiguration) Specifies configuration information about the labels input, including its S3 location.labelsInputConfiguration
(LabelsInputConfiguration labelsInputConfiguration) Specifies configuration information about the labels input, including its S3 location.lastUpdatedTime
(Instant lastUpdatedTime) Indicates the last time the machine learning model was updated.latestScheduledRetrainingAvailableDataInDays
(Integer latestScheduledRetrainingAvailableDataInDays) Indicates the number of days of data used in the most recent scheduled retraining run.latestScheduledRetrainingFailedReason
(String latestScheduledRetrainingFailedReason) If the model version was generated by retraining and the training failed, this indicates the reason for that failure.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 being described.default DescribeModelResponse.Builder
modelDiagnosticsOutputConfiguration
(Consumer<ModelDiagnosticsOutputConfiguration.Builder> modelDiagnosticsOutputConfiguration) Configuration information for the model's pointwise model diagnostics.modelDiagnosticsOutputConfiguration
(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration) Configuration information for the model's pointwise model diagnostics.modelMetrics
(String modelMetrics) The Model Metrics show an aggregated summary of the model's performance within the evaluation time range.The name of the machine learning model being described.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.modelVersionActivatedAt
(Instant modelVersionActivatedAt) The date the active model version was activated.nextScheduledRetrainingStartDate
(Instant nextScheduledRetrainingStartDate) Indicates the date and time that the next scheduled retraining run will start on.offCondition
(String offCondition) Indicates that the asset associated with this sensor has been shut off.previousActiveModelVersion
(Long previousActiveModelVersion) The model version that was set as the active model version prior to the current active model version.previousActiveModelVersionArn
(String previousActiveModelVersionArn) The ARN of the model version that was set as the active model version prior to the current active model version.previousModelVersionActivatedAt
(Instant previousModelVersionActivatedAt) The date and time when the previous active model version was activated.priorModelMetrics
(String priorModelMetrics) If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range.retrainingSchedulerStatus
(String retrainingSchedulerStatus) Indicates the status of the retraining scheduler.retrainingSchedulerStatus
(RetrainingSchedulerStatus retrainingSchedulerStatus) Indicates the status of the retraining scheduler.The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.A JSON description of the data that is in each time series dataset, including names, column names, and data types.serverSideKmsKeyId
(String serverSideKmsKeyId) Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.sourceModelVersionArn
(String sourceModelVersionArn) The Amazon Resource Name (ARN) of the source model version.Specifies the current status of the model being described.status
(ModelStatus status) Specifies the current status of the model being described.trainingDataEndTime
(Instant trainingDataEndTime) Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.trainingDataStartTime
(Instant trainingDataStartTime) Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.trainingExecutionEndTime
(Instant trainingExecutionEndTime) Indicates the time at which the training of the machine learning model was completed.trainingExecutionStartTime
(Instant trainingExecutionStartTime) Indicates the time at which the training of the machine learning model began.Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copy
Methods inherited from interface software.amazon.awssdk.services.lookoutequipment.model.LookoutEquipmentResponse.Builder
build, responseMetadata, responseMetadata
Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
Methods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields
Methods inherited from interface software.amazon.awssdk.core.SdkResponse.Builder
sdkHttpResponse, sdkHttpResponse
-
Method Details
-
modelName
The name of the machine learning model being described.
- Parameters:
modelName
- The name of the machine learning model being described.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
modelArn
The Amazon Resource Name (ARN) of the machine learning model being described.
- Parameters:
modelArn
- The Amazon Resource Name (ARN) of the machine learning model being described.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
datasetName
The name of the dataset being used by the machine learning being described.
- Parameters:
datasetName
- The name of the dataset being used by the machine learning being described.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
datasetArn
The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
- Parameters:
datasetArn
- The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
schema
A JSON description of the data that is in each time series dataset, including names, column names, and data types.
- Parameters:
schema
- A JSON description of the data that is in each time series dataset, including names, column names, and data types.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
labelsInputConfiguration
DescribeModelResponse.Builder labelsInputConfiguration(LabelsInputConfiguration labelsInputConfiguration) Specifies configuration information about the labels input, including its S3 location.
- Parameters:
labelsInputConfiguration
- Specifies configuration information about the labels input, including its S3 location.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
labelsInputConfiguration
default DescribeModelResponse.Builder labelsInputConfiguration(Consumer<LabelsInputConfiguration.Builder> labelsInputConfiguration) Specifies configuration information about the labels input, including its S3 location.
This is a convenience method that creates an instance of theLabelsInputConfiguration.Builder
avoiding the need to create one manually viaLabelsInputConfiguration.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tolabelsInputConfiguration(LabelsInputConfiguration)
.- Parameters:
labelsInputConfiguration
- a consumer that will call methods onLabelsInputConfiguration.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
trainingDataStartTime
Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
- Parameters:
trainingDataStartTime
- Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
trainingDataEndTime
Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
- Parameters:
trainingDataEndTime
- Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
evaluationDataStartTime
Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
- Parameters:
evaluationDataStartTime
- Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
evaluationDataEndTime
Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
- Parameters:
evaluationDataEndTime
- Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
roleArn
The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
- Parameters:
roleArn
- The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
dataPreProcessingConfiguration
DescribeModelResponse.Builder dataPreProcessingConfiguration(DataPreProcessingConfiguration dataPreProcessingConfiguration) The configuration is the
TargetSamplingRate
, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, theTargetSamplingRate
is 1 minute.When providing a value for the
TargetSamplingRate
, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H- Parameters:
dataPreProcessingConfiguration
- The configuration is theTargetSamplingRate
, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, theTargetSamplingRate
is 1 minute.When providing a value for the
TargetSamplingRate
, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
dataPreProcessingConfiguration
default DescribeModelResponse.Builder dataPreProcessingConfiguration(Consumer<DataPreProcessingConfiguration.Builder> dataPreProcessingConfiguration) The configuration is the
TargetSamplingRate
, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, theTargetSamplingRate
is 1 minute.When providing a value for the
This is a convenience method that creates an instance of theTargetSamplingRate
, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1HDataPreProcessingConfiguration.Builder
avoiding the need to create one manually viaDataPreProcessingConfiguration.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed todataPreProcessingConfiguration(DataPreProcessingConfiguration)
.- Parameters:
dataPreProcessingConfiguration
- a consumer that will call methods onDataPreProcessingConfiguration.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
status
Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
- Parameters:
status
- Specifies the current status of the model being described. Status describes the status of the most recent action of the model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
status
Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
- Parameters:
status
- Specifies the current status of the model being described. Status describes the status of the most recent action of the model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
trainingExecutionStartTime
Indicates the time at which the training of the machine learning model began.
- Parameters:
trainingExecutionStartTime
- Indicates the time at which the training of the machine learning model began.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
trainingExecutionEndTime
Indicates the time at which the training of the machine learning model was completed.
- Parameters:
trainingExecutionEndTime
- Indicates the time at which the training of the machine learning model was completed.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
failedReason
If the training of the machine learning model failed, this indicates the reason for that failure.
- Parameters:
failedReason
- If the training of the machine learning model failed, this indicates the reason for that failure.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
modelMetrics
The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.
- Parameters:
modelMetrics
- The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
lastUpdatedTime
Indicates the last time the machine learning model was updated. The type of update is not specified.
- Parameters:
lastUpdatedTime
- Indicates the last time the machine learning model was updated. The type of update is not specified.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
createdAt
Indicates the time and date at which the machine learning model was created.
- Parameters:
createdAt
- Indicates the time and date at which the machine learning model was created.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
serverSideKmsKeyId
Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
- Parameters:
serverSideKmsKeyId
- Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
offCondition
Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
- Parameters:
offCondition
- Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
sourceModelVersionArn
The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.
- Parameters:
sourceModelVersionArn
- The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
importJobStartTime
The date and time when the import job was started. This field appears if the active model version was imported.
- Parameters:
importJobStartTime
- The date and time when the import job was started. This field appears if the active model version was imported.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
importJobEndTime
The date and time when the import job was completed. This field appears if the active model version was imported.
- Parameters:
importJobEndTime
- The date and time when the import job was completed. This field appears if the active model version was imported.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
activeModelVersion
The name of the model version used by the inference schedular when running a scheduled inference execution.
- Parameters:
activeModelVersion
- The name of the model version used by the inference schedular when running a scheduled inference execution.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
activeModelVersionArn
The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
- Parameters:
activeModelVersionArn
- The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
modelVersionActivatedAt
The date the active model version was activated.
- Parameters:
modelVersionActivatedAt
- The date the active model version was activated.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
previousActiveModelVersion
The model version that was set as the active model version prior to the current active model version.
- Parameters:
previousActiveModelVersion
- The model version that was set as the active model version prior to the current active model version.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
previousActiveModelVersionArn
The ARN of the model version that was set as the active model version prior to the current active model version.
- Parameters:
previousActiveModelVersionArn
- The ARN of the model version that was set as the active model version prior to the current active model version.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
previousModelVersionActivatedAt
DescribeModelResponse.Builder previousModelVersionActivatedAt(Instant previousModelVersionActivatedAt) The date and time when the previous active model version was activated.
- Parameters:
previousModelVersionActivatedAt
- The date and time when the previous active model version was activated.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
priorModelMetrics
If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.
- Parameters:
priorModelMetrics
- If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
latestScheduledRetrainingFailedReason
DescribeModelResponse.Builder latestScheduledRetrainingFailedReason(String latestScheduledRetrainingFailedReason) If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
- Parameters:
latestScheduledRetrainingFailedReason
- If the model version was generated by retraining and the training failed, this indicates the reason for that failure.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
latestScheduledRetrainingStatus
DescribeModelResponse.Builder latestScheduledRetrainingStatus(String 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:
-
latestScheduledRetrainingStatus
DescribeModelResponse.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:
-
latestScheduledRetrainingModelVersion
DescribeModelResponse.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.
-
latestScheduledRetrainingStartTime
DescribeModelResponse.Builder latestScheduledRetrainingStartTime(Instant latestScheduledRetrainingStartTime) Indicates 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.
-
latestScheduledRetrainingAvailableDataInDays
DescribeModelResponse.Builder latestScheduledRetrainingAvailableDataInDays(Integer latestScheduledRetrainingAvailableDataInDays) Indicates the number of days of data used in the most recent scheduled retraining run.
- Parameters:
latestScheduledRetrainingAvailableDataInDays
- Indicates the number of days of data used in the most recent scheduled retraining run.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
nextScheduledRetrainingStartDate
DescribeModelResponse.Builder nextScheduledRetrainingStartDate(Instant nextScheduledRetrainingStartDate) Indicates the date and time 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 and time 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.
-
accumulatedInferenceDataStartTime
DescribeModelResponse.Builder accumulatedInferenceDataStartTime(Instant accumulatedInferenceDataStartTime) Indicates the start time of the inference data that has been accumulated.
- Parameters:
accumulatedInferenceDataStartTime
- Indicates the start time of the inference data that has been accumulated.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
accumulatedInferenceDataEndTime
DescribeModelResponse.Builder accumulatedInferenceDataEndTime(Instant accumulatedInferenceDataEndTime) Indicates the end time of the inference data that has been accumulated.
- Parameters:
accumulatedInferenceDataEndTime
- Indicates the end time of the inference data that has been accumulated.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
retrainingSchedulerStatus
Indicates 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:
-
retrainingSchedulerStatus
DescribeModelResponse.Builder retrainingSchedulerStatus(RetrainingSchedulerStatus retrainingSchedulerStatus) Indicates 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:
-
modelDiagnosticsOutputConfiguration
DescribeModelResponse.Builder modelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration) Configuration information for the model's pointwise model diagnostics.
- Parameters:
modelDiagnosticsOutputConfiguration
- Configuration information for the model's pointwise model diagnostics.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
modelDiagnosticsOutputConfiguration
default DescribeModelResponse.Builder modelDiagnosticsOutputConfiguration(Consumer<ModelDiagnosticsOutputConfiguration.Builder> modelDiagnosticsOutputConfiguration) Configuration information for the model's pointwise model diagnostics.
This is a convenience method that creates an instance of theModelDiagnosticsOutputConfiguration.Builder
avoiding the need to create one manually viaModelDiagnosticsOutputConfiguration.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tomodelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration)
.- Parameters:
modelDiagnosticsOutputConfiguration
- a consumer that will call methods onModelDiagnosticsOutputConfiguration.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
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 isQUALITY_THRESHOLD_MET
.If the model is unlabeled, the model quality can't be assessed and the value of
ModelQuality
isCANNOT_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 isPOOR_QUALITY_DETECTED
. Otherwise, the value isQUALITY_THRESHOLD_MET
.If the model is unlabeled, the model quality can't be assessed and the value of
ModelQuality
isCANNOT_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:
-
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 isQUALITY_THRESHOLD_MET
.If the model is unlabeled, the model quality can't be assessed and the value of
ModelQuality
isCANNOT_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 isPOOR_QUALITY_DETECTED
. Otherwise, the value isQUALITY_THRESHOLD_MET
.If the model is unlabeled, the model quality can't be assessed and the value of
ModelQuality
isCANNOT_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:
-