How to determine which deep learning method was used by Azure AutoML in a classification task?

Question

I am a non-data scientist / clinical researcher using Azure AutoML to predict binary and multi-class classification using features from patient records. I have been able to run my experiments using the Azure ML Studio UI. Deep learning is enabled for all my experiments.

Now, I have to write about the work I have done and have managed to understand how to report the scaling and normalisation used and ML algorithm selected when running AutoML.

However, I cannot find anything on how the deep learning feature was applied. I have looked through the documentation and have searched online.

I know that the deep learning used by Azure AutoML could be one of the following:

1. Platt Scaling
2. Isotonic Regression
3. Temperature Scaling
4. Bayesian Calibration
5. Ensemble Calibration

But I can't find out which one is being used on my dataset. =(