https://github.com/bgreenwell/fastshap

Fast approximate Shapley values in R
https://github.com/bgreenwell/fastshap

explainable-ai explainable-ml interpretable-machine-learning shapley shapley-values variable-importance xai

Last synced: 9 days ago
JSON representation

Fast approximate Shapley values in R

• Host: GitHub
• URL: https://github.com/bgreenwell/fastshap
• Owner: bgreenwell
• Created: 2019-07-17T14:20:31.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-02-22T21:48:53.000Z (9 months ago)
• Last Synced: 2024-10-24T00:40:45.240Z (16 days ago)
• Topics: explainable-ai, explainable-ml, interpretable-machine-learning, shapley, shapley-values, variable-importance, xai
• Language: R
• Homepage: https://bgreenwell.github.io/fastshap/
• Size: 99.4 MB
• Stars: 115
• Watchers: 4
• Forks: 18
• Open Issues: 12
• Metadata Files:
  • Readme: README.Rmd

Awesome Lists containing this project

• AwesomeResponsibleAI - fastshap

README

        
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  fig.align = "center",

  out.width = "100%",

  message = FALSE,

  warning = FALSE

)

```

# fastshap 

[![CRAN status](https://www.r-pkg.org/badges/version/fastshap)](https://CRAN.R-project.org/package=fastshap)

[![R-CMD-check](https://github.com/bgreenwell/fastshap/workflows/R-CMD-check/badge.svg)](https://github.com/bgreenwell/fastshap/actions)

[![Codecov test coverage](https://codecov.io/gh/bgreenwell/fastshap/branch/master/graph/badge.svg)](https://codecov.io/gh/bgreenwell/fastshap?branch=master)

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)

[![R-CMD-check](https://github.com/bgreenwell/fastshap/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/bgreenwell/fastshap/actions/workflows/R-CMD-check.yaml)

The goal of **fastshap** is to provide an efficient and speedy approach (at least relative to other implementations) for computing approximate Shapley values, which help explain the predictions from any machine learning model. 

![](https://media.giphy.com/media/26AHLNr8en8J3ovOo/giphy.gif)

## Installation

``` r

# Install the latest stable version from CRAN:

install.packages("fastshap")

# Install the latest development version from GitHub:

if (!requireNamespace("remotes")) {

  install.packages("remotes")

}

remotes::install_github("bgreenwell/fastshap")

```