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CreateModelRequest

Source code in docs_src/capo_lookoutequipment/types/create_model_request.py
class CreateModelRequest(TypedDict, closed=True):
    model_name: "capo_lookoutequipment.types.model_name.ModelName"
    """<p>The name for the machine learning model to be created.</p>"""
    dataset_name: "capo_lookoutequipment.types.dataset_identifier.DatasetIdentifier"
    """<p>The name of the dataset for the machine learning model being created. </p>"""
    dataset_schema: NotRequired[
        "capo_lookoutequipment.types.dataset_schema.DatasetSchema"
    ]
    """<p>The data schema for the machine learning model being created. </p>"""
    labels_input_configuration: NotRequired[
        "capo_lookoutequipment.types.labels_input_configuration.LabelsInputConfiguration"
    ]
    """<p>The input configuration for the labels being used for the machine learning model that's being created. </p>"""
    client_token: "capo_lookoutequipment.types.idempotence_token.IdempotenceToken"
    """<p>A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. </p>"""
    training_data_start_time: NotRequired[
        "capo_lookoutequipment.types.timestamp.Timestamp"
    ]
    """<p>Indicates the time reference in the dataset that should be used to begin the subset of training data for the machine learning model. </p>"""
    training_data_end_time: NotRequired[
        "capo_lookoutequipment.types.timestamp.Timestamp"
    ]
    """<p>Indicates the time reference in the dataset that should be used to end the subset of training data for the machine learning model. </p>"""
    evaluation_data_start_time: NotRequired[
        "capo_lookoutequipment.types.timestamp.Timestamp"
    ]
    """<p>Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the machine learning model. </p>"""
    evaluation_data_end_time: NotRequired[
        "capo_lookoutequipment.types.timestamp.Timestamp"
    ]
    """<p> Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the machine learning model. </p>"""
    role_arn: NotRequired["capo_lookoutequipment.types.iam_role_arn.IamRoleArn"]
    """<p> The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model. </p>"""
    data_pre_processing_configuration: NotRequired[
        "capo_lookoutequipment.types.data_pre_processing_configuration.DataPreProcessingConfiguration"
    ]
    """<p>The configuration is the <code>TargetSamplingRate</code>, 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 <code>TargetSamplingRate</code> is 1 minute.</p> <p>When providing a value for the <code>TargetSamplingRate</code>, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore <i>PT1S</i>, the value for a 15 minute rate is <i>PT15M</i>, and the value for a 1 hour rate is <i>PT1H</i> </p>"""
    server_side_kms_key_id: NotRequired[
        "capo_lookoutequipment.types.name_or_arn.NameOrArn"
    ]
    """<p>Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment. </p>"""
    tags: NotRequired["capo_lookoutequipment.types.tag_list.TagList"]
    """<p> Any tags associated with the machine learning model being created. </p>"""
    off_condition: NotRequired["capo_lookoutequipment.types.off_condition.OffCondition"]
    """<p>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.</p>"""
    model_diagnostics_output_configuration: NotRequired[
        "capo_lookoutequipment.types.model_diagnostics_output_configuration.ModelDiagnosticsOutputConfiguration"
    ]
    """<p>The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics. You must also specify the <code>RoleArn</code> request parameter.</p>"""

client_token instance-attribute

client_token: IdempotenceToken

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

data_pre_processing_configuration instance-attribute

data_pre_processing_configuration: NotRequired[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, 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

dataset_name instance-attribute

dataset_name: DatasetIdentifier

The name of the dataset for the machine learning model being created.

dataset_schema instance-attribute

dataset_schema: NotRequired[DatasetSchema]

The data schema for the machine learning model being created.

evaluation_data_end_time instance-attribute

evaluation_data_end_time: NotRequired[Timestamp]

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

evaluation_data_start_time instance-attribute

evaluation_data_start_time: NotRequired[Timestamp]

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

labels_input_configuration instance-attribute

labels_input_configuration: NotRequired[LabelsInputConfiguration]

The input configuration for the labels being used for the machine learning model that's being created.

model_diagnostics_output_configuration instance-attribute

model_diagnostics_output_configuration: NotRequired[ModelDiagnosticsOutputConfiguration]

The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics. You must also specify the RoleArn request parameter.

model_name instance-attribute

model_name: ModelName

The name for the machine learning model to be created.

off_condition instance-attribute

off_condition: NotRequired[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.

role_arn instance-attribute

role_arn: NotRequired[IamRoleArn]

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

server_side_kms_key_id instance-attribute

server_side_kms_key_id: NotRequired[NameOrArn]

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

tags instance-attribute

tags: NotRequired[TagList]

Any tags associated with the machine learning model being created.

training_data_end_time instance-attribute

training_data_end_time: NotRequired[Timestamp]

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

training_data_start_time instance-attribute

training_data_start_time: NotRequired[Timestamp]

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