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:
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Nested Class Summary
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Method Summary
Modifier and TypeMethodDescriptionfinal Long
The model version that the inference scheduler uses to run an inference execution.final String
The Amazon Resource Name (ARN) of the model version that is set as active.static ModelSummary.Builder
builder()
final Instant
The time at which the specific model was created.final String
The Amazon Resource Name (ARN) of the dataset used to create the model.final String
The name of the dataset being used for the machine learning model.final boolean
final boolean
equalsBySdkFields
(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 int
hashCode()
final Long
Indicates the most recent model version that was generated by retraining.final Instant
Indicates the start time of the most recent scheduled retraining run.final ModelVersionStatus
Indicates the status of the most recent scheduled retraining run.final String
Indicates the status of the most recent scheduled retraining run.final String
modelArn()
The Amazon Resource Name (ARN) of the machine learning model.Returns the value of the ModelDiagnosticsOutputConfiguration property for this object.final String
The name of the machine learning model.final ModelQuality
Provides a quality assessment for a model that uses labels.final String
Provides a quality assessment for a model that uses labels.final Instant
Indicates the date that the next scheduled retraining run will start on.Indicates the status of the retraining scheduler.final String
Indicates the status of the retraining scheduler.static Class
<? extends ModelSummary.Builder> final ModelStatus
status()
Indicates the status of the machine learning model.final String
Indicates 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 String
toString()
Returns a string representation of this object.Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy
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Method Details
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modelName
The name of the machine learning model.
- Returns:
- The name of the machine learning model.
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modelArn
The Amazon Resource Name (ARN) of the machine learning model.
- Returns:
- The Amazon Resource Name (ARN) of the machine learning model.
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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.
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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.
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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,
status
will 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:
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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,
status
will 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:
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createdAt
The time at which the specific model was created.
- Returns:
- The time at which the specific model was created.
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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.
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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.
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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,
latestScheduledRetrainingStatus
will 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:
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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,
latestScheduledRetrainingStatus
will 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:
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latestScheduledRetrainingModelVersion
Indicates the most recent model version that was generated by retraining.
- Returns:
- Indicates the most recent model version that was generated by retraining.
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latestScheduledRetrainingStartTime
Indicates the start time of the most recent scheduled retraining run.
- Returns:
- Indicates the start time of the most recent scheduled retraining run.
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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.
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retrainingSchedulerStatus
Indicates the status of the retraining scheduler.
If the service returns an enum value that is not available in the current SDK version,
retrainingSchedulerStatus
will 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:
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retrainingSchedulerStatusAsString
Indicates the status of the retraining scheduler.
If the service returns an enum value that is not available in the current SDK version,
retrainingSchedulerStatus
will 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:
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modelDiagnosticsOutputConfiguration
Returns the value of the ModelDiagnosticsOutputConfiguration property for this object.- Returns:
- The value of the ModelDiagnosticsOutputConfiguration property for this object.
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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.
If the service returns an enum value that is not available in the current SDK version,
modelQuality
will 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
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.
- See Also:
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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
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.
If the service returns an enum value that is not available in the current SDK version,
modelQuality
will 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
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.
- See Also:
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toBuilder
Description copied from interface:ToCopyableBuilder
Take this object and create a builder that contains all of the current property values of this object.- Specified by:
toBuilder
in interfaceToCopyableBuilder<ModelSummary.Builder,
ModelSummary> - Returns:
- a builder for type T
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builder
-
serializableBuilderClass
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hashCode
public final int hashCode() -
equals
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equalsBySdkFields
Description copied from interface:SdkPojo
Indicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in anSdkPojo
class, and is generated based on a service model.If an
SdkPojo
class does not have any inherited fields,equalsBySdkFields
andequals
are essentially the same.- Specified by:
equalsBySdkFields
in interfaceSdkPojo
- Parameters:
obj
- the object to be compared with- Returns:
- true if the other object equals to this object by sdk fields, false otherwise.
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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. -
getValueForField
-
sdkFields
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