Metadata-Version: 2.0
Name: fastshapv1
Version: 0.0.10
Summary: A shap wrapper for fastai
Home-page: https://github.com/muellerzr/fastshapv1
Author: Zach Mueller
Author-email: muellerzr@gmail.com
License: Apache Software License 2.0
Keywords: f,a,s,t,a,i,2, ,s,h,a,p
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: fastai
Requires-Dist: fastcore
Requires-Dist: shap

# FastSHAP (V1)
> This project brings in part of the `SHAP` library into `fastai` (V1) and make it compatible. Thank you to Nestor Demeure for his assistance with the project!

## Install

`pip install fastshap`

## How to use

First we'll quickly train a `ADULTS` tabular model

```
from fastai2.tabular.all import *
```

```
path = untar_data(URLs.ADULT_SAMPLE)
df = pd.read_csv(path/'adult.csv')
```

```
dep_var = 'salary'
cat_names = ['workclass', 'education', 'marital-status', 'occupation', 'relationship', 'race']
cont_names = ['age', 'fnlwgt', 'education-num']
procs = [Categorify, FillMissing, Normalize]
```

```
splits = IndexSplitter(list(range(800,1000)))(range_of(df))
to = TabularPandas(df, procs, cat_names, cont_names, y_names="salary", splits=splits)
dls = to.dataloaders()
```

```
learn = tabular_learner(dls, layers=[200,100], metrics=accuracy)
learn.fit(1, 1e-2)
```

And now for some example usage!

```
from fastshap.interp import *
```

```
exp = ShapInterpretation(learn, df.iloc[:100])
```

```
exp.dependence_plot('age')
```


    Classification model detected, displaying score for the class <50k.
    (use `class_id` to specify another class)



![png](docs/images/output_13_2.png)


For more examples see [01_Interpret](https://muellerzr.github.io/fastshap//interpret)


*For more unofficial fastai extensions, see the [Fastai Extensions Repository](https://github.com/nestordemeure/fastai-extensions-repository).*


