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You are using the Azure Machine Learning SDK to run a training experiment that trains a classification model and calculates its accuracy metric. The model will be retrained monthly as new data becomes available. You must register the model for use in a batch inference pipeline and ensure that models from subsequent retraining experiments are registered only if their accuracy is higher than the currently registered model.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.