Hi,
TF-DF models are not calibrated by default, and automated calibration is (currently) not available in the open source version. The amount of calibration/non-calibration of a model is dependent on the learning algorithm (e.g. RF or GBT) and the hyper-parameters. For example, the classification Random Forest with default hyper-parameter is certainly not calibrated.
A solution is to train a calibration model on top of the model. For example, (1) you can learn an isotonic regression 2 with the Pava algorithm, or (2) train a piece-wise linear function with Gradient descent using TF-Latice 2.
Cheers,