fastshapv1 0.0.10

# 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)


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).