FastSHAP
This project brings in part of the
SHAPlibrary intofastai2and 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.