Delete make_pipeline_from_components - #2218
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## main #2218 +/- ##
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- Coverage 100.0% 100.0% -0.0%
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Files 287 287
Lines 24451 24399 -52
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- Hits 24433 24381 -52
Misses 18 18
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freddyaboulton
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freddyaboulton
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Looks great @angela97lin ! I love the net deletion of lines hehe
| return base_class(complete_component_graph, parameters=parameters, custom_hyperparameters=custom_hyperparameters) | ||
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| def make_pipeline_from_components(component_instances, problem_type, custom_name=None, random_seed=0): |
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I'm debating whether we should keep this around for another release and instead issue a deprecation warning in this pr.
I'm ok with deleting this util, I don't think it got a lot of traction from users but just noting that I think we use a different process for deleting functions/methods.
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Interesting point, but I'm okay deleting immediately, since I think the main use of this was internal alignment :p Plus, it's not too difficult to do what make_pipeline_from_components with our new pipelines so not too much lost there!
| base_pipeline_class = RegressionPipeline | ||
| stacking_component_name = StackedEnsembleRegressor.name | ||
| input_pipelines = [make_pipeline_from_components([regressor], problem_type) for regressor in stackable_regressors] | ||
| input_pipelines = [base_pipeline_class([regressor]) for regressor in stackable_regressors] |
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nit-pick: I don't think there's a need for base_pipeline_class anymore.
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Hmmm, I think we still need it for the line after (depending on which problem type, we create a specific pipeline class) but I'm okay with updating this line to just use RegressionPipeline so it's more clear! 😁
bchen1116
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LGTM! Agree with Freddy that it might be useful to deprecate before immediately removing from EvalML
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Closes #2173