Although one can call predict_mode on a probabilistic binary
classifier to get deterministic predictions, a more flexible strategy
is to wrap the model using BinaryThresholdPredictor, as this allows
the user to specify the threshold probability for predicting a
positive class. This wrapping converts a probablistic classifer into a
deterministic one.
The positive class is always the second class returned when calling
levels on the training target y.
MLJModels.BinaryThresholdPredictor