From d555e9fa358f7ea9e3a5c7f52e750c1cf0f8f9b5 Mon Sep 17 00:00:00 2001 From: christopherbunn Date: Tue, 31 Oct 2023 01:27:32 -0400 Subject: [PATCH] Use feature names final --- .../pipelines/multiseries_regression_pipeline.py | 16 ++++------------ 1 file changed, 4 insertions(+), 12 deletions(-) diff --git a/evalml/pipelines/multiseries_regression_pipeline.py b/evalml/pipelines/multiseries_regression_pipeline.py index 35621fadfb..d76951db4d 100644 --- 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,