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CreateEvaluationInput

Source code in docs_src/capo_machine_learning/types/create_evaluation_input.py 
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class CreateEvaluationInput(TypedDict, closed=True):
    evaluation_id: "capo_machine_learning.types.entity_id.EntityId"
    """<p>A user-supplied ID that uniquely identifies the <code>Evaluation</code>.</p>"""
    evaluation_name: NotRequired["capo_machine_learning.types.entity_name.EntityName"]
    """<p>A user-supplied name or description of the <code>Evaluation</code>.</p>"""
    ml_model_id: "capo_machine_learning.types.entity_id.EntityId"
    """<p>The ID of the <code>MLModel</code> to evaluate.</p> <p>The schema used in creating the <code>MLModel</code> must match the schema of the <code>DataSource</code> used in the <code>Evaluation</code>.</p>"""
    evaluation_data_source_id: "capo_machine_learning.types.entity_id.EntityId"
    """<p>The ID of the <code>DataSource</code> for the evaluation. The schema of the <code>DataSource</code> must match the schema used to create the <code>MLModel</code>.</p>"""

evaluation_data_source_id instance-attribute 

evaluation_data_source_id: EntityId

The ID of the DataSource for the evaluation. The schema of the DataSource must match the schema used to create the MLModel.

evaluation_id instance-attribute 

evaluation_id: EntityId

A user-supplied ID that uniquely identifies the Evaluation.

evaluation_name instance-attribute 

evaluation_name: NotRequired[EntityName]

A user-supplied name or description of the Evaluation.

ml_model_id instance-attribute 

ml_model_id: EntityId

The ID of the MLModel to evaluate.

The schema used in creating the MLModel must match the schema of the DataSource used in the Evaluation.