Class ModelSummary
- All Implemented Interfaces:
Serializable,SdkPojo,ToCopyableBuilder<ModelSummary.Builder,ModelSummary>
Provides information about the specified machine learning model, including dataset and model names and ARNs, as well as status.
- See Also:
-
Nested Class Summary
Nested Classes -
Method Summary
Modifier and TypeMethodDescriptionfinal LongThe model version that the inference scheduler uses to run an inference execution.final StringThe Amazon Resource Name (ARN) of the model version that is set as active.static ModelSummary.Builderbuilder()final InstantThe time at which the specific model was created.final StringThe Amazon Resource Name (ARN) of the dataset used to create the model.final StringThe name of the dataset being used for the machine learning model.final booleanfinal booleanequalsBySdkFields(Object obj) Indicates whether some other object is "equal to" this one by SDK fields.final <T> Optional<T> getValueForField(String fieldName, Class<T> clazz) final inthashCode()final LongIndicates the most recent model version that was generated by retraining.final InstantIndicates the start time of the most recent scheduled retraining run.final ModelVersionStatusIndicates the status of the most recent scheduled retraining run.final StringIndicates the status of the most recent scheduled retraining run.final StringmodelArn()The Amazon Resource Name (ARN) of the machine learning model.Returns the value of the ModelDiagnosticsOutputConfiguration property for this object.final StringThe name of the machine learning model.final ModelQualityProvides a quality assessment for a model that uses labels.final StringProvides a quality assessment for a model that uses labels.final InstantIndicates the date that the next scheduled retraining run will start on.Indicates the status of the retraining scheduler.final StringIndicates the status of the retraining scheduler.static Class<? extends ModelSummary.Builder> final ModelStatusstatus()Indicates the status of the machine learning model.final StringIndicates the status of the machine learning model.Take this object and create a builder that contains all of the current property values of this object.final StringtoString()Returns a string representation of this object.Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy
-
Method Details
-
modelName
The name of the machine learning model.
- Returns:
- The name of the machine learning model.
-
modelArn
The Amazon Resource Name (ARN) of the machine learning model.
- Returns:
- The Amazon Resource Name (ARN) of the machine learning model.
-
datasetName
The name of the dataset being used for the machine learning model.
- Returns:
- The name of the dataset being used for the machine learning model.
-
datasetArn
The Amazon Resource Name (ARN) of the dataset used to create the model.
- Returns:
- The Amazon Resource Name (ARN) of the dataset used to create the model.
-
status
Indicates the status of the machine learning model.
If the service returns an enum value that is not available in the current SDK version,
statuswill returnModelStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromstatusAsString().- Returns:
- Indicates the status of the machine learning model.
- See Also:
-
statusAsString
Indicates the status of the machine learning model.
If the service returns an enum value that is not available in the current SDK version,
statuswill returnModelStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromstatusAsString().- Returns:
- Indicates the status of the machine learning model.
- See Also:
-
createdAt
The time at which the specific model was created.
- Returns:
- The time at which the specific model was created.
-
activeModelVersion
The model version that the inference scheduler uses to run an inference execution.
- Returns:
- The model version that the inference scheduler uses to run an inference execution.
-
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:
- 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.
-
latestScheduledRetrainingStatus
Indicates the status of the most recent scheduled retraining run.
If the service returns an enum value that is not available in the current SDK version,
latestScheduledRetrainingStatuswill returnModelVersionStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromlatestScheduledRetrainingStatusAsString().- Returns:
- Indicates the status of the most recent scheduled retraining run.
- See Also:
-
latestScheduledRetrainingStatusAsString
Indicates the status of the most recent scheduled retraining run.
If the service returns an enum value that is not available in the current SDK version,
latestScheduledRetrainingStatuswill returnModelVersionStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromlatestScheduledRetrainingStatusAsString().- Returns:
- Indicates the status of the most recent scheduled retraining run.
- See Also:
-
latestScheduledRetrainingModelVersion
Indicates the most recent model version that was generated by retraining.
- Returns:
- Indicates the most recent model version that was generated by retraining.
-
latestScheduledRetrainingStartTime
Indicates the start time of the most recent scheduled retraining run.
- Returns:
- Indicates the start time of the most recent scheduled retraining run.
-
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:
- 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.
-
retrainingSchedulerStatus
Indicates the status of the retraining scheduler.
If the service returns an enum value that is not available in the current SDK version,
retrainingSchedulerStatuswill returnRetrainingSchedulerStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromretrainingSchedulerStatusAsString().- Returns:
- Indicates the status of the retraining scheduler.
- See Also:
-
retrainingSchedulerStatusAsString
Indicates the status of the retraining scheduler.
If the service returns an enum value that is not available in the current SDK version,
retrainingSchedulerStatuswill returnRetrainingSchedulerStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromretrainingSchedulerStatusAsString().- Returns:
- Indicates the status of the retraining scheduler.
- See Also:
-
modelDiagnosticsOutputConfiguration
Returns the value of the ModelDiagnosticsOutputConfiguration property for this object.- Returns:
- The value of the ModelDiagnosticsOutputConfiguration property for this object.
-
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
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.
If the service returns an enum value that is not available in the current SDK version,
modelQualitywill returnModelQuality.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available frommodelQualityAsString().- Returns:
- 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
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.
- See Also:
-
modelQualityAsString
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
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.
If the service returns an enum value that is not available in the current SDK version,
modelQualitywill returnModelQuality.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available frommodelQualityAsString().- Returns:
- 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
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.
- See Also:
-
toBuilder
Description copied from interface:ToCopyableBuilderTake this object and create a builder that contains all of the current property values of this object.- Specified by:
toBuilderin interfaceToCopyableBuilder<ModelSummary.Builder,ModelSummary> - Returns:
- a builder for type T
-
builder
-
serializableBuilderClass
-
hashCode
-
equals
-
equalsBySdkFields
Description copied from interface:SdkPojoIndicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in anSdkPojoclass, and is generated based on a service model.If an
SdkPojoclass does not have any inherited fields,equalsBySdkFieldsandequalsare essentially the same.- Specified by:
equalsBySdkFieldsin interfaceSdkPojo- Parameters:
obj- the object to be compared with- Returns:
- true if the other object equals to this object by sdk fields, false otherwise.
-
toString
-
getValueForField
-
sdkFields
-
sdkFieldNameToField
- Specified by:
sdkFieldNameToFieldin interfaceSdkPojo- Returns:
- The mapping between the field name and its corresponding field.
-