fix(MetaLabeling): previously misinterpreted meta-labeling, now also multiplying base model's prediction with the meta model's prediction (#193)

* fix(MetaLabeling): previously misinterpreted meta-labeling, now also multiplying base model's prediction with the meta model's prediction

* fix(Evaluate): print results

* fix(Evaluate): make sure we have numerical stability in returns

* fix(Inference): only output and print stats in training mode

* fix(Evaluate): don't add miniscule amount to result

tests/test_evaluation.py

@@ -100,7 +100,6 @@ def test_evaluation():
         y_pred=processed_predictions_to_match_returns,
         y_true=y,
         no_of_classes='two',
-        print_results = False,
         discretize=True
     )