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Add STLDecomposer to multiseries pipelines #4299
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@@ -442,6 +442,7 @@ def inverse_transform( | |
y.append(y_series) | ||
y_df = pd.DataFrame(y).T | ||
y_df.index = original_index | ||
y_df.columns = y_t.columns | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Out of curiosity, why is this necessary? What was the situation where the columns weren't the same? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The predictions weren't getting the corresponding series ID values as the column names and that's needed since the decomposer uses this to select the correct value. Before this was causing the decomposer to return NaN values. @christopherbunn figured that out so he might have more info. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The predictions that are generated do not have the series ID values as their column names. Copying these names over is required so we can inverse_transform from the decomposer. |
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return y_df | ||
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def get_trend_dataframe(self, X, y): | ||
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This is hard to follow 😅 can you add an explanatory comment?