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ModelVersionSummary

Source code in docs_src/capo_lookoutequipment/types/model_version_summary.py 
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class ModelVersionSummary(TypedDict, closed=True):
    model_name: NotRequired["capo_lookoutequipment.types.model_name.ModelName"]
    """<p>The name of the model that this model version is a version of.</p>"""
    model_arn: NotRequired["capo_lookoutequipment.types.model_arn.ModelArn"]
    """<p>The Amazon Resource Name (ARN) of the model that this model version is a version of.</p>"""
    model_version: NotRequired["capo_lookoutequipment.types.model_version.ModelVersion"]
    """<p>The version of the model.</p>"""
    model_version_arn: NotRequired[
        "capo_lookoutequipment.types.model_version_arn.ModelVersionArn"
    ]
    """<p>The Amazon Resource Name (ARN) of the model version.</p>"""
    created_at: NotRequired["capo_lookoutequipment.types.timestamp.Timestamp"]
    """<p>The time when this model version was created.</p>"""
    status: NotRequired[
        "capo_lookoutequipment.types.model_version_status.ModelVersionStatus"
    ]
    """<p>The current status of the model version.</p>"""
    source_type: NotRequired[
        "capo_lookoutequipment.types.model_version_source_type.ModelVersionSourceType"
    ]
    """<p>Indicates how this model version was generated.</p>"""
    model_quality: NotRequired["capo_lookoutequipment.types.model_quality.ModelQuality"]
    """<p>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 <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is <code>QUALITY_THRESHOLD_MET</code>. </p> <p>If the model is unlabeled, the model quality can't be assessed and the value of <code>ModelQuality</code> is <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.</p> <p>For information about improving the quality of a model, see <a href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html">Best practices with Amazon Lookout for Equipment</a>.</p>"""

created_at instance-attribute 

created_at: NotRequired[Timestamp]

The time when this model version was created.

model_arn instance-attribute 

model_arn: NotRequired[ModelArn]

The Amazon Resource Name (ARN) of the model that this model version is a version of.

model_name instance-attribute 

model_name: NotRequired[ModelName]

The name of the model that this model version is a version of.

model_quality instance-attribute 

model_quality: NotRequired[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 ModelQuality is 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 improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

model_version instance-attribute 

model_version: NotRequired[ModelVersion]

The version of the model.

model_version_arn instance-attribute 

model_version_arn: NotRequired[ModelVersionArn]

The Amazon Resource Name (ARN) of the model version.

source_type instance-attribute 

source_type: NotRequired[ModelVersionSourceType]

Indicates how this model version was generated.

status instance-attribute 

status: NotRequired[ModelVersionStatus]

The current status of the model version.