FastSHAP

This project brings in part of the SHAP library into fastai2 and make it compatable. 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

For more unofficial fastai extensions, see the Fastai Extensions Repository.