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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{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 <img src='man/figures/logo-fastshap.png' align="right" height="139" />
<!-- badges: start -->
[![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)
<!-- badges: end -->
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")
```