shap · PyPI

A unified approach to explain the output of any machine learning model.

Project description

SHAP (SHapley Additive exPlanations) is a unified approach to explain the output of any machine learning model. SHAP connects game theory with local explanations, uniting several previous methods and representing the only possible consistent and locally accurate additive feature attribution method based on expectations.

Project details

Release history Release notifications | RSS feed

0.47.2

Apr 17, 2025

0.47.1

Mar 22, 2025

0.47.0

Mar 5, 2025

0.46.0

Jun 27, 2024

0.45.1

May 7, 2024

0.45.0

Mar 8, 2024

0.44.1

Jan 25, 2024

0.44.0

Dec 7, 2023

0.43.0

Oct 9, 2023

0.42.1

Jul 15, 2023

0.42.0

Jul 6, 2023

0.41.0

Jun 16, 2022

0.40.0

Oct 20, 2021

0.39.0

Mar 3, 2021

0.38.1

Jan 15, 2021

0.37.0

Nov 4, 2020

0.36.0

Aug 27, 2020

0.35.0

Feb 27, 2020

0.34.0

Dec 27, 2019

0.33.0

Dec 11, 2019

0.32.1

Nov 6, 2019

0.32.0

Nov 6, 2019

0.31.0

Oct 21, 2019

0.30.2

Sep 30, 2019

0.30.1

Sep 9, 2019

0.30.0

Aug 31, 2019

0.29.3

Jun 19, 2019

0.29.2

Jun 19, 2019

0.29.1

May 15, 2019

0.28.6

May 14, 2019

0.28.5

Feb 16, 2019

0.28.4

Feb 16, 2019

0.28.3

Jan 24, 2019

0.28.2

Jan 23, 2019

0.28.1

Jan 23, 2019

0.28.0

Jan 21, 2019

0.27.0

Jan 1, 2019

This version

0.26.0

Dec 12, 2018

0.25.2

Nov 9, 2018

0.25.1

Nov 8, 2018

0.25.0

Nov 7, 2018

0.24.0

Aug 24, 2018

0.23.2

Aug 24, 2018

0.23.1

Aug 16, 2018

0.23.0

Aug 16, 2018

0.22.3

Aug 9, 2018

0.22.2

Aug 8, 2018

0.22.1

Aug 8, 2018

0.22.0

Aug 8, 2018

0.21.0

Jul 24, 2018

0.20.2

Jul 23, 2018

0.20.1

Jul 17, 2018

0.19.5

Jul 13, 2018

0.19.4

Jul 12, 2018

0.19.3

Jul 7, 2018

0.19.2

Jun 29, 2018

0.19.1

Jun 28, 2018

0.18.1

Jun 7, 2018

0.18.0

Jun 7, 2018

0.17.1

May 30, 2018

0.17.0

May 29, 2018

0.16.1

May 21, 2018

0.15.0

May 3, 2018

0.14.1

Apr 19, 2018

0.14.0

Apr 14, 2018

0.13.7

Apr 12, 2018

0.13.6

Apr 11, 2018

0.13.5

Apr 11, 2018

0.13.3

Apr 10, 2018

0.13.2

Apr 10, 2018

0.13.1

Apr 10, 2018

0.13

Apr 9, 2018

0.12.1

Apr 5, 2018

0.12.0

Mar 22, 2018

0.11.1

Mar 7, 2018

0.11.0

Mar 3, 2018

0.10.3

Feb 20, 2018

0.10.2

Feb 19, 2018

0.10.1

Feb 15, 2018

0.10.0

Feb 13, 2018

0.9.1

Feb 12, 2018

0.8.9

Feb 7, 2018

0.8.8

Feb 5, 2018

0.8.7

Feb 2, 2018

0.8.6

Feb 1, 2018

0.8.5

Jan 31, 2018

0.8.4

Jan 31, 2018

0.8.3

Jan 29, 2018

0.8.2

Jan 29, 2018

0.8.1

Jan 29, 2018

0.8.0

Jan 23, 2018

0.7.0

Dec 7, 2017

0.6.1

Dec 1, 2017

0.6

Nov 23, 2017

0.5

Oct 25, 2017

0.3.3

Oct 4, 2017

0.3.2

Oct 3, 2017

0.3.1

Sep 26, 2017

0.3

Sep 21, 2017

0.2.4

May 18, 2017

0.2.3

Apr 18, 2017

0.2.2

Apr 14, 2017

0.2.1

Dec 9, 2016

0.2

Dec 1, 2016

0.1.2

Dec 1, 2016

0.1

Dec 1, 2016

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