DescribeModel

The name of the machine learning model to be described.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 200.

Pattern: ^[0-9a-zA-Z_-]{1,200}$

Required: Yes

Indicates the end time of the inference data that has been accumulated.

Type: Timestamp

Indicates the start time of the inference data that has been accumulated.

Type: Timestamp

The name of the model version used by the inference schedular when running a scheduled inference execution.

Type: Long

Valid Range: Minimum value of 1.

The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws(-[^:]+)?:lookoutequipment:[a-zA-Z0-9\-]*:[0-9]{12}:model\/[0-9a-zA-Z_-]{1,200}\/.+\/model-version\/[0-9]{1,}$

Indicates the time and date at which the machine learning model was created.

Type: Timestamp

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, the TargetSamplingRate 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

Type: DataPreProcessingConfiguration object

The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: arn:aws(-[^:]+)?:lookoutequipment:[a-zA-Z0-9\-]*:[0-9]{12}:dataset\/[0-9a-zA-Z_-]{1,200}\/.+

The name of the dataset being used by the machine learning being described.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 200.

Pattern: ^[0-9a-zA-Z_-]{1,200}$

Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.

Type: Timestamp

Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.

Type: Timestamp

If the training of the machine learning model failed, this indicates the reason for that failure.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 5000.

Pattern: [\P{M}\p{M}]{1,5000}

The date and time when the import job was completed. This field appears if the active model version was imported.

Type: Timestamp

The date and time when the import job was started. This field appears if the active model version was imported.

Type: Timestamp

Specifies configuration information about the labels input, including its S3 location.

Type: LabelsInputConfiguration object

Indicates the last time the machine learning model was updated. The type of update is not specified.

Type: Timestamp

Indicates the number of days of data used in the most recent scheduled retraining run.

Type: Integer

If the model version was generated by retraining and the training failed, this indicates the reason for that failure.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 5000.

Pattern: [\P{M}\p{M}]{1,5000}

Indicates the most recent model version that was generated by retraining.

Type: Long

Valid Range: Minimum value of 1.

Indicates the start time of the most recent scheduled retraining run.

Type: Timestamp

Indicates the status of the most recent scheduled retraining run.

Type: String

Valid Values: IN_PROGRESS | SUCCESS | FAILED | IMPORT_IN_PROGRESS | CANCELED

The Amazon Resource Name (ARN) of the machine learning model being described.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: arn:aws(-[^:]+)?:lookoutequipment:[a-zA-Z0-9\-]*:[0-9]{12}:model\/.+

Configuration information for the model's pointwise model diagnostics.

Type: ModelDiagnosticsOutputConfiguration object

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.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 50000.

The name of the machine learning model being described.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 200.

Pattern: ^[0-9a-zA-Z_-]{1,200}$

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 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.

Type: String

Valid Values: QUALITY_THRESHOLD_MET | CANNOT_DETERMINE_QUALITY | POOR_QUALITY_DETECTED

The date the active model version was activated.

Type: Timestamp

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.

Type: Timestamp

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.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 2048.

The model version that was set as the active model version prior to the current active model version.

Type: Long

Valid Range: Minimum value of 1.

The ARN of the model version that was set as the active model version prior to the current active model version.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws(-[^:]+)?:lookoutequipment:[a-zA-Z0-9\-]*:[0-9]{12}:model\/[0-9a-zA-Z_-]{1,200}\/.+\/model-version\/[0-9]{1,}$

The date and time when the previous active model version was activated.

Type: Timestamp

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.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 50000.

Indicates the status of the retraining scheduler.

Type: String

Valid Values: PENDING | RUNNING | STOPPING | STOPPED

The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: arn:aws(-[^:]+)?:iam::[0-9]{12}:role/.+

A JSON description of the data that is in each time series dataset, including names, column names, and data types.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 1000000.

Provides the identifier of the AWS KMS key used to encrypt model data by Amazon Lookout for Equipment.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 1024.

Pattern: arn:aws[a-z\-]*:kms:[a-z0-9\-]*:\d{12}:[\w\-\/]+

The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws(-[^:]+)?:lookoutequipment:[a-zA-Z0-9\-]*:[0-9]{12}:model\/[0-9a-zA-Z_-]{1,200}\/.+\/model-version\/[0-9]{1,}$

Specifies the current status of the model being described. Status describes the status of the most recent action of the model.

Type: String

Valid Values: IN_PROGRESS | SUCCESS | FAILED | IMPORT_IN_PROGRESS

Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.

Type: Timestamp

Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.

Type: Timestamp

Indicates the time at which the training of the machine learning model was completed.

Type: Timestamp

Indicates the time at which the training of the machine learning model began.

Type: Timestamp

The request could not be completed because you do not have access to the resource.

HTTP Status Code: 400

Processing of the request has failed because of an unknown error, exception or failure.

HTTP Status Code: 500

The resource requested could not be found. Verify the resource ID and retry your request.

HTTP Status Code: 400

The request was denied due to request throttling.

HTTP Status Code: 400

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related AWS service that's being utilized.

HTTP Status Code: 400