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Merged
solegalli merged 8 commits into from
Feb 8, 2022
Merged

specifies image url, fixes docs #357

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76117ce
specifies umage url
solegalli Jan 4, 2022
0bd7e45
removes typo drop psi selection
solegalli Jan 4, 2022
1222d22
specifies umage url
solegalli Jan 4, 2022
4dfe00b
add datetime to readme
solegalli Jan 4, 2022
b1265b0
modifies repo linked in setup file
solegalli Jan 4, 2022
807c4b1
updates license
solegalli Jan 31, 2022
f5d62a1
adds dsf video
solegalli Feb 2, 2022
8ba738e
fixes docs warning
solegalli Feb 8, 2022
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2 changes: 1 addition & 1 deletion LICENSE.md
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BSD 3-Clause License

Copyright (c) 2018-2021 The Feature-engine developers.
Copyright (c) 2018-2022 The Feature-engine developers.
All rights reserved.

Redistribution and use in source and binary forms, with or without
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7 changes: 5 additions & 2 deletions README.md
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Expand Up @@ -14,7 +14,7 @@
[![DOI](https://joss.theoj.org/papers/10.21105/joss.03642/status.svg)](https://doi.org/10.21105/joss.03642)


[<img src="./docs/images/logo/FeatureEngine.png" width="248">](http://feature-engine.readthedocs.io)
[<img src="https://github.com/feature-engine/feature_engine/blob/main/docs/images/logo/FeatureEngine.png" width="248">](http://feature-engine.readthedocs.io)

Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models.
Feature-engine's transformers follow Scikit-learn's functionality with fit() and transform() methods to learn the
Expand Down Expand Up @@ -120,6 +120,9 @@ transforming parameters from the data and then transform it.
* RecursiveFeatureAddition
* DropHighPSIFeatures

### Datetime
* DatetimeFeatures

### Preprocessing
* MatchVariables

Expand Down Expand Up @@ -218,5 +221,5 @@ BSD 3-Clause

## Donate

[Sponsor the maintainer](https://github.com/sponsors/solegalli) to support her continue expanding
[Sponsor us](https://github.com/sponsors/solegalli) to support her continue expanding
Feature-engine.
1 change: 1 addition & 0 deletions docs/resources/blogs.rst
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Videos
------

- `Streamlining Feature Engineering Pipes with Feature-engine <https://www.youtube.com/watch?v=0V3_uXX30Ko>`_, Data Science Festival, 2020.
- `Optimising Feature Engineering Pipelines with Feature-engine <https://www.youtube.com/watch?v=qT-3KUaFYmk/>`_, Pydata Cambridge 2020, from minute 51:43.


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2 changes: 1 addition & 1 deletion docs/user_guide/selection/DropHighPSIFeatures.rst
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6).. _psi_selection:
.. _psi_selection:

.. currentmodule:: feature_engine.selection

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2 changes: 2 additions & 0 deletions feature_engine/selection/drop_psi_features.py
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Expand Up @@ -65,6 +65,8 @@ class DropHighPSIFeatures(BaseSelector):
values in the list, will go to the basis set, and the remaining ones to the test
set.

More details in the :ref:`User Guide <psi_selection>`.

References
----------
https://scholarworks.wmich.edu/cgi/viewcontent.cgi?article=4249&context=dissertations
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2 changes: 1 addition & 1 deletion setup.py
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# Package meta-data.
NAME = "feature_engine"
DESCRIPTION = "Feature engineering package with Scikit-learn's fit transform functionality"
URL = "http://github.com/solegalli/feature_engine"
URL = "http://github.com/feature-engine/feature_engine"
EMAIL = "solegalli@protonmail.com"
AUTHOR = "Soledad Galli"
REQUIRES_PYTHON = ">=3.6.0"
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