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Surpress warnings in target encoder #3540

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merged 2 commits into from Jun 3, 2022
Merged

Surpress warnings in target encoder #3540

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d119f07
Surpress warnings in target encoder
freddyaboulton Jun 3, 2022
0d7d84b
Add to release notes
freddyaboulton Jun 3, 2022
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1 change: 1 addition & 0 deletions docs/source/release_notes.rst
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Expand Up @@ -4,6 +4,7 @@ Release Notes
* Enhancements
* Fixes
* Fixed github workflows for featuretools and woodwork to test their main branch against evalml. :pr:`3517`
* Supress warnings in ``TargetEncoder`` raised by a coming change to default parameters :pr:`3540`
* Changes
* Transitioned to use pyproject.toml and setup.cfg away from setup.py :pr:`3494`, :pr:`3536`
* Documentation Changes
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11 changes: 9 additions & 2 deletions evalml/pipelines/components/transformers/encoders/target_encoder.py
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@@ -1,4 +1,6 @@
"""A transformer that encodes categorical features into target encodings."""
import warnings

import pandas as pd

from ..transformer import Transformer
Expand Down Expand Up @@ -31,7 +33,7 @@ class TargetEncoder(Transformer, metaclass=OneHotEncoderMeta):
def __init__(
self,
cols=None,
smoothing=1.0,
smoothing=1,
handle_unknown="value",
handle_missing="value",
random_seed=0,
Expand Down Expand Up @@ -65,9 +67,14 @@ def __init__(
"category_encoders",
error_msg="category_encoders not installed. Please install using `pip install category_encoders`",
)
# Supress warnings for now due to problems discussion here:
# https://github.com/scikit-learn-contrib/category_encoders/issues/327
with warnings.catch_warnings():
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We could also change the default value of smoothing and add min_samples_leaf parameter but there is still some discussion as to what the new defaults should be so figured it was better to suppress the warnings

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agreed!

warnings.simplefilter("ignore")
encoder = category_encode.target_encoder.TargetEncoder(**parameters)
super().__init__(
parameters=parameters,
component_obj=category_encode.target_encoder.TargetEncoder(**parameters),
component_obj=encoder,
random_seed=random_seed,
)

Expand Down