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Ability to use more meta-learner models for stacked ensembles #1739

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dsherry opened this issue Jan 26, 2021 · 3 comments
Open

Ability to use more meta-learner models for stacked ensembles #1739

dsherry opened this issue Jan 26, 2021 · 3 comments
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new feature Features which don't yet exist. performance Issues tracking performance improvements.

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@dsherry
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dsherry commented Jan 26, 2021

We currently use logistic reg for classification and linear reg for regression. I bet lasso would perform better!

@dsherry dsherry added enhancement An improvement to an existing feature. performance Issues tracking performance improvements. labels Jan 26, 2021
@angela97lin
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FWIW, the default for scikit-learn is RidgeCV (https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingRegressor.html); I had gone with the linear regressor since we don't have an impl of this in EvalML yet!

@dsherry dsherry added new feature Features which don't yet exist. and removed enhancement An improvement to an existing feature. labels Mar 11, 2021
@dsherry
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dsherry commented Apr 29, 2021

Note @angela97lin did some testing of this for #2093. It looked promising.

@freddyaboulton
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Based on #2660, I think we should use ElasticNet as the meta-learner for ensembles.

FYI @christopherbunn

@tyler3991 tyler3991 changed the title Ability to use lasso or ridge as the meta-learner for stacked ensembles Ability to use more meta-learner models for stacked ensembles Oct 13, 2021
@asniyaz asniyaz self-assigned this Feb 16, 2022
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