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[AIR] Add KBinsDiscretizer #28389

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Sep 16, 2022
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[AIR] Add KBinsDiscretizer #28389

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711bfec
[AIR] Add `KBinsDiscretizer`
Yard1 Sep 8, 2022
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Add docs
Yard1 Sep 8, 2022
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Cleanup
Yard1 Sep 8, 2022
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Merge branch 'master' into add_kbins_discretizer
Yard1 Sep 15, 2022
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1 change: 1 addition & 0 deletions doc/source/custom_directives.py
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Expand Up @@ -60,6 +60,7 @@ def update_context(app, pagename, templatename, context, doctree):
"dask.distributed",
"datasets",
"datasets.iterable_dataset",
"datasets.load",
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"gym",
"gym.spaces",
"horovod",
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9 changes: 9 additions & 0 deletions doc/source/ray-air/package-ref.rst
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Expand Up @@ -74,6 +74,15 @@ Feature Scalers
.. autoclass:: ray.data.preprocessors.StandardScaler
:show-inheritance:

K-Bins Discretizers
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Would a more-general Discretizers be better? I see sklearn does something similar in their user guide https://scikit-learn.org/stable/modules/preprocessing.html#discretization

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Sure, makes sense!

###################

.. autoclass:: ray.data.preprocessors.CustomKBinsDiscretizer
:show-inheritance:

.. autoclass:: ray.data.preprocessors.UniformKBinsDiscretizer
:show-inheritance:
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Text Encoders
#############

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6 changes: 6 additions & 0 deletions python/ray/data/preprocessors/__init__.py
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Expand Up @@ -20,6 +20,10 @@
from ray.data.preprocessors.tokenizer import Tokenizer
from ray.data.preprocessors.transformer import PowerTransformer
from ray.data.preprocessors.vectorizer import CountVectorizer, HashingVectorizer
from ray.data.preprocessors.discretizer import (
CustomKBinsDiscretizer,
UniformKBinsDiscretizer,
)

__all__ = [
"BatchMapper",
Expand All @@ -41,4 +45,6 @@
"StandardScaler",
"Concatenator",
"Tokenizer",
"CustomKBinsDiscretizer",
"UniformKBinsDiscretizer",
]
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