Use feature names final

alteryx · Oct 31, 2023 · d555e9f · d555e9f
1 parent 8d623cb
commit d555e9f
Showing 1 changed file with 4 additions and 12 deletions.
diff --git a/evalml/pipelines/multiseries_regression_pipeline.py b/evalml/pipelines/multiseries_regression_pipeline.py
@@ -129,29 +129,21 @@ def predict_in_sample(
             self.input_target_name,
         )
         # Order series columns to be same as expected input feature names
+        X_unstacked = X_unstacked[list(self.input_feature_names.values())[0]]
+        X_train_unstacked = X_train_unstacked[
+            list(self.input_feature_names.values())[0]
+        ]
         y_unstacked = y_unstacked[
             y_train_unstacked.columns.intersection(y_unstacked.columns)
         ]
         y_train_unstacked = y_train_unstacked[
             y_train_unstacked.columns.intersection(y_unstacked.columns)
         ]
-
-        X_unstacked = X_unstacked[list(self.input_feature_names.values())[0]]
-        X_train_unstacked = X_train_unstacked[
-            list(self.input_feature_names.values())[0]
-        ]
-
         X_train_unstacked = infer_feature_types(X_train_unstacked)
         y_train_unstacked = infer_feature_types(y_train_unstacked)
         X_unstacked = infer_feature_types(X_unstacked)
         y_unstacked = infer_feature_types(y_unstacked)
 
-        print("X_uns", X_unstacked, X_unstacked.ww.schema)
-        print("y_uns", y_unstacked, y_unstacked.ww.schema)
-        print("Xtr_uns", X_train_unstacked, X_train_unstacked.ww.schema)
-        print("ytr_uns", y_train_unstacked, y_train_unstacked.ww.schema)
-        print(self.component_graph._input_types)
-
         unstacked_predictions = super().predict_in_sample(
             X_unstacked,
             y_unstacked,