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Feature(Speed): Python launches faster by conditionally importing models. (#169)

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* feat: Added optional import of models.

* fix: Models weren't wrapped into abstract class, fixed it.

* chore: Deleted leftover comments.

* fix: Same merge commit as on remote.

* fix: System wasn't putting in RF because there was no differentiation between RF as regressor and RF as classificator.

* fix(Models): use the XGBoostModel wrapper

Co-authored-by: Daniel Szemerey <szemereydaniel@gmail.com>
Co-authored-by: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>
This commit is contained in:
Daniel Szemerey
2022-01-14 14:29:24 +01:00
committed by GitHub
co-authored by Daniel Szemerey Mark Aron Szulyovszky
parent 797d45d036
commit 31dc847be1
8 changed files with 119 additions and 77 deletions
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sweep_primary_models.yaml
+1 -1
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@@ -45,7 +45,7 @@ parameters:
index_column:
value: 'int'
primary_models:
values: [['LR_two_class'], ['SVC'], ['LDA'], ['KNN'], ['CART'], ['MNB'], ['NB'], ['AB'], ['RF'], ['XGB_two_class'], ['LGBM']]
values: [['LR_two_class'], ['SVC'], ['LDA'], ['KNN'], ['CART'], ['MNB'], ['NB'], ['AB'], ['RFC'], ['XGB_two_class'], ['LGBM']]
distribution: categorical
meta_labeling_models:
value: ["LGBM", "LR_two_class"]