SIENTIAPDE-1430: Introduce comprehensive integration testing with JSON-based scenarios and detailed README documentation. Enhance training workflow to support advanced model configurations, including polynomial regression with mandatory scaler validation. Ensure robust prediction handling by calculating training predictions (y_train_pred) before denormalization and automatically configuring datetime indices for time-series operations.

tests/utils/models/test_train_model_result.py

@@ -183,11 +183,11 @@ def test_train_model_result_is_dataclass(sample_params, sample_dataframes):
 
 
 def test_train_model_result_field_count():
-    """Test that TrainModelResult has exactly 19 fields."""
+    """Test that TrainModelResult has exactly 20 fields."""
     from dataclasses import fields
 
     result_fields = fields(TrainModelResult)
-    assert len(result_fields) == 19
+    assert len(result_fields) == 20
 
     field_names = {f.name for f in result_fields}
     expected_fields = {
@@ -200,6 +200,7 @@ def test_train_model_result_field_count():
         'regr',
         'scaler_dict',
         'y_pred',
+        'y_train_pred',
         'mse_val',
         'mae_val',
         'r2_val',