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Add StandardScaler to ElasticNet pipelines. #1065

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merged 3 commits into from Aug 17, 2020
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Add StandardScaler to ElasticNet pipelines. #1065

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d5b394d
All linear models have a standard scaler in the pipeline.
freddyaboulton Aug 14, 2020
7c7f7ef
Edited release_notes for PR 1065.
freddyaboulton Aug 14, 2020
0dabc81
Adding test to make sure EN pipelines have a StandardScaler.
freddyaboulton Aug 14, 2020
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1 change: 1 addition & 0 deletions docs/source/release_notes.rst
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Expand Up @@ -11,6 +11,7 @@ Release Notes
* Fixes
* Updated TextFeaturizer component to no longer require an internet connection to run :pr:`1022`
* Fixed non-deterministic element of TextFeaturizer transformations :pr:`1022`
* Added a StandardScaler to all ElasticNet pipelines :pr:`1065`
* Changes
* Added `needs_fitting` property to ComponentBase :pr:`1044`
* Updated references to data types to use datatype lists defined in `evalml.utils.gen_utils` :pr:`1039`
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5 changes: 2 additions & 3 deletions evalml/pipelines/utils.py
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Expand Up @@ -6,14 +6,13 @@
)
from .regression_pipeline import RegressionPipeline

from evalml.model_family import ModelFamily
from evalml.pipelines.components import (
CatBoostClassifier,
CatBoostRegressor,
DateTimeFeaturizer,
DropNullColumns,
Imputer,
LinearRegressor,
LogisticRegressionClassifier,
OneHotEncoder,
StandardScaler
)
Expand Down Expand Up @@ -56,7 +55,7 @@ def _get_preprocessing_components(X, y, problem_type, estimator_class):
if (add_datetime_featurizer or len(categorical_cols.columns) > 0) and estimator_class not in {CatBoostClassifier, CatBoostRegressor}:
pp_components.append(OneHotEncoder)

if estimator_class in {LinearRegressor, LogisticRegressionClassifier}:
if estimator_class.model_family == ModelFamily.LINEAR_MODEL:
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Nice! Could we add a test (testing test_make_pipeline) to make sure :d

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Certainly!

pp_components.append(StandardScaler)
return pp_components

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