def METHOD_NAME(
    self, dataset: Tuple[Input, Input, str], experiment_name: str, add_validation: bool = False
) -> ClassificationJob:
    # Get training and validation data
    training_data, validation_data, label_column_name = dataset
    classification_task = classification(
        training_data=training_data,
        target_column_name=label_column_name,
        primary_metric="accuracy",
        compute="automl-cpu-cluster",
        experiment_name=experiment_name,
        properties=get_automl_job_properties(),
    )
    if add_validation:
        classification_task.set_data(
            training_data=training_data, validation_data=validation_data, target_column_name=label_column_name
        )
    classification_task.set_limits(
        trial_timeout_minutes=10,
        timeout_minutes=600,
        max_trials=1,
        max_concurrent_trials=1,
        enable_early_termination=True,
    )
    classification_task.set_training(enable_stack_ensemble=False, enable_vote_ensemble=False)
    return classification_task