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I recommend keeping either one or the other to avoid possible confusion.
Keeping make_column_transformer means more editing in the present contents but will reduce variance naming (and therefore calling) the transformers. What do you think?
The text was updated successfully, but these errors were encountered:
I recommend keeping either one or the other to avoid possible confusion.
I would use both but make sure that we present both. We should have the same issue with Pipeline and make_pipeline. I see that we do a slightly better job stating that make_pipeline is creating a Pipeline. But I think it would be worth showing how to create a Pipeline directly.
The reason to use both is that there are time where you want to use one or another, specifically.
Most of the notebooks use
ColumnTransformer
glossary.md
predictive_modeling_module_take_away.md:
wrap_up_quiz 1
03_categorical_pipeline_column_transformer.py
03_categorical_pipeline_ex_02.py
03_categorical_pipeline_sol_02.py
parameter_tuning_ex_02.py and parameter_tuning_sol_02.py
parameter_tuning_ex_03.py and parameter_tuning_sol_03.py
parameter_tuning_grid_search.py
parameter_tuning_nested.py
parameter_tuning_randomized_search.py
On the other hand,
make_column_transformer
is only used inensemble_random_forest.py
wrap_up_quiz 1
wrap_up_quiz 4
wrap_up_quiz 5
I recommend keeping either one or the other to avoid possible confusion.
Keeping
make_column_transformer
means more editing in the present contents but will reduce variance naming (and therefore calling) the transformers. What do you think?The text was updated successfully, but these errors were encountered: