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Merge pull request #145 from yg79/feature/v1.2.0
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Feature/v1.2.0
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yg79 authored Mar 10, 2021
2 parents 07452d5 + 48c8253 commit e601c37
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5 changes: 5 additions & 0 deletions README.md
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Expand Up @@ -19,6 +19,11 @@ It provides several types of visualization that display explicit labels that eve
Data Scientists can more easily understand their models and share their results. End users can understand the decision proposed by a model using a summary of the most influential criteria.

- Readthedocs: [![documentation badge](https://readthedocs.org/projects/shapash/badge/?version=latest)](https://shapash.readthedocs.io/en/latest/)
- Medium: [Towards AI](https://pub.towardsai.net/shapash-making-ml-models-understandable-by-everyone-8f96ad469eb3)
- Presentation video for french speakers:
<p align="center">
<a href="https://www.youtube.com/watch?v=r1R_A9B9apk" target="_blank"><img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/webinar_screenshot.png" width="550" alt="French Webinar"/></a>
</p>

<br/> <br/>

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7 changes: 1 addition & 6 deletions docs/tutorials/tutorial01-Shapash-Overview-Launch-WebApp.rst
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Expand Up @@ -105,10 +105,6 @@ Model Fitting
regressor = LGBMRegressor(n_estimators=200).fit(Xtrain,ytrain)
.. code:: ipython
y_pred = pd.DataFrame(regressor.predict(Xtest),columns=['pred'],index=Xtest.index)
Understanding my model with shapash
-----------------------------------

Expand All @@ -128,8 +124,7 @@ Declare and Compile SmartExplainer
xpl.compile(
x=Xtest,
model=regressor,
preprocessing=encoder, # Optional: compile step can use inverse_transform method
y_pred=y_pred # Optional
preprocessing=encoder # Optional: compile step can use inverse_transform method
)
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2 changes: 1 addition & 1 deletion setup.cfg
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@@ -1,5 +1,5 @@
[bumpversion]
current_version = 1.1.0
current_version = 1.2.0
commit = True
tag = True

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2 changes: 1 addition & 1 deletion setup.py
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Expand Up @@ -30,7 +30,7 @@

setup(
name="shapash", # Replace with your own username
version="1.1.0",
version="1.2.0",
python_requires='>3.5, < 3.9',
url='https://github.com/MAIF/shapash',
author="Yann Golhen, Sebastien Bidault, Yann Lagre, Maxime Gendre",
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2 changes: 1 addition & 1 deletion shapash/__init__.py
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Expand Up @@ -3,4 +3,4 @@

__author__ = """Yann Golhen, Yann Lagré, Sebastien Bidault, Maxime Gendre, Thomas Bouche, Johann Martin"""
__email__ = '[email protected], [email protected], [email protected], [email protected]'
__version__ = '1.1.0'
__version__ = '1.2.0'
14 changes: 2 additions & 12 deletions tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb
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Expand Up @@ -389,15 +389,6 @@
"regressor = LGBMRegressor(n_estimators=200).fit(Xtrain,ytrain)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"y_pred = pd.DataFrame(regressor.predict(Xtest),columns=['pred'],index=Xtest.index)"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down Expand Up @@ -447,8 +438,7 @@
"xpl.compile(\n",
" x=Xtest,\n",
" model=regressor,\n",
" preprocessing=encoder, # Optional: compile step can use inverse_transform method\n",
" y_pred=y_pred # Optional\n",
" preprocessing=encoder # Optional: compile step can use inverse_transform method\n",
")"
]
},
Expand Down Expand Up @@ -699,4 +689,4 @@
},
"nbformat": 4,
"nbformat_minor": 4
}
}

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