Make covariate column names explicit #34
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abdulfatir
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abdulfatir
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Thanks @shchur! This will make the task definitions more transparent and easy to check which columns are actually used by a model.
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| future_known = future_data.remove_columns(self.target_columns_list + self.past_dynamic_columns) | ||
| test = future_data.select_columns([self.id_column, self.timestamp_column] + self.target_columns_list) | ||
| future_known = future_data.remove_columns(self.target_columns + self.past_dynamic_columns) |
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Should we specifically only select known future columns (+ id and timestamp) here after removing past and target_columns?
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It looks like all other columns are removed during data loading, so maybe this is not needed?
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I have updated load_full_dataset to not remove any columns, and to only perform column removal before the split. This makes it easy to check what columns are available in the dataset using public API.
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Description of changes:
__version__stored in__init__.pyknown_dynamic_columns,past_dynamic_columns,static_columnsexplicit properties of theTaskinstead of automatically inferring them from data.target_column->targetto make the name more consistent withstr | list[str]typing.Task.target_columns_list->target_columns.To do
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