A consistent interface to make predictions from this model.

def get_transform(self, model_output):
        """ A consistent interface to make predictions from this model.
        """
        if model_output == "margin":
            transform = "identity"
        elif model_output == "probability":
            if self.tree_output == "log_odds":
                transform = "logistic"
            elif self.tree_output == "probability":
                transform = "identity"
            else:
                raise Exception("model_output = \"probability\" is not yet supported when model.tree_output = \"" + self.tree_output + "\"!")
        elif model_output == "logloss":

            if self.objective == "squared_error":
                transform = "squared_loss"
            elif self.objective == "binary_crossentropy":
                transform = "logistic_nlogloss"
            else:
                raise Exception("model_output = \"logloss\" is not yet supported when model.objective = \"" + self.objective + "\"!")
        return transform