feat(Data): add option to predict 3 classes (#79)

* feat(Data): add option to predict 3 classes

* feat(Evaluation): added ability to evaluate 3 class predictions

* chore(Config): set sensible config for regression models

* feat(Data): added option to use balanced or imbalanced three-class data

* feat(Evaluate): correctly track "no_of_samples" now that we have three classes

* chore(Sweep): remove probably not useful scaler values from sweep

tests/test_evaluation.py

@@ -85,7 +85,9 @@ def test_evaluation():
         model_name='test',
         target_returns=fake_target_returns,
         y_pred=processed_predictions_to_match_returns,
-        method='classification'
+        y_true=y,
+        method='classification',
+        no_of_classes='two'
     )
 
     assert result['accuracy'] == 100.0