lime

Local Interpretable Model-Agnostic Explanations (R port of original Python package)

https://github.com/thomasp85/lime

Science Score: 20.0%

This score indicates how likely this project is to be science-related based on various indicators:

○
CITATION.cff file
○
codemeta.json file
○
.zenodo.json file
○
DOI references
✓
Academic publication links
Links to: arxiv.org
✓
Committers with academic emails
1 of 16 committers (6.3%) from academic institutions
○
Institutional organization owner
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (18.4%) to scientific vocabulary

Keywords

caret model-checking model-evaluation modeling r

Keywords from Contributors

tidy-data setup tidyverse parsing fwf csv documentation-tool package-creation http-mock visualisation

Last synced: 6 months ago · JSON representation

Repository

Local Interpretable Model-Agnostic Explanations (R port of original Python package)

Basic Info

Host: GitHub
Owner: thomasp85
License: other
Language: R
Default Branch: main
Homepage: https://lime.data-imaginist.com/
Size: 10.6 MB

Statistics

Stars: 488
Watchers: 30
Forks: 109
Open Issues: 51
Releases: 0

Topics

caret model-checking model-evaluation modeling r

Created almost 9 years ago · Last pushed over 3 years ago

Metadata Files

Readme License Code of conduct

README.Rmd

---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-"
)
```

# lime 


[![R-CMD-check](https://github.com/thomasp85/lime/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/thomasp85/lime/actions/workflows/R-CMD-check.yaml)
[![Codecov test coverage](https://codecov.io/gh/thomasp85/lime/branch/main/graph/badge.svg)](https://app.codecov.io/gh/thomasp85/lime?branch=main)
[![CRAN_Release_Badge](http://www.r-pkg.org/badges/version-ago/lime)](https://CRAN.R-project.org/package=lime)
[![CRAN_Download_Badge](http://cranlogs.r-pkg.org/badges/lime)](https://CRAN.R-project.org/package=lime)


> There once was a package called lime,
>
> Whose models were simply sublime,  
>
> It gave explanations for their variations, 
>
> one observation at a time.
 
*lime-rick by Mara Averick*

* * *

*This is an R port of the Python lime package (https://github.com/marcotcr/lime)
developed by the authors of the lime (Local Interpretable Model-agnostic 
Explanations) approach for black-box model explanations. All credits for the
invention of the approach goes to the original developers.*

The purpose of `lime` is to explain the predictions of black box classifiers. 
What this means is that for any given prediction and any given classifier it is
able to determine a small set of features in the original data that has driven
the outcome of the prediction. To learn more about the methodology of `lime` 
read the [paper](https://arxiv.org/abs/1602.04938) and visit the repository of
the [original implementation](https://github.com/marcotcr/lime).

The `lime` package for R does not aim to be a line-by-line port of its Python
counterpart. Instead it takes the ideas laid out in the original code and 
implements them in an API that is idiomatic to R.

## An example
Out of the box `lime` supports a long range of models, e.g. those created with
caret, parsnip, and mlr. Support for unsupported models are easy to achieve by 
adding a `predict_model` and `model_type` method for the given model.

The following shows how a random forest model is trained on the iris data set 
and how `lime` is then used to explain a set of new observations:

```{r, message=FALSE, fig.asp=1}
library(caret)
library(lime)

# Split up the data set
iris_test <- iris[1:5, 1:4]
iris_train <- iris[-(1:5), 1:4]
iris_lab <- iris[[5]][-(1:5)]

# Create Random Forest model on iris data
model <- train(iris_train, iris_lab, method = 'rf')

# Create an explainer object
explainer <- lime(iris_train, model)

# Explain new observation
explanation <- explain(iris_test, explainer, n_labels = 1, n_features = 2)

# The output is provided in a consistent tabular format and includes the
# output from the model.
explanation

# And can be visualised directly
plot_features(explanation)
```

`lime` also supports explaining image and text models. For image explanations 
the relevant areas in an image can be highlighted:

```{r, fig.asp=0.5}
explanation <- .load_image_example()

plot_image_explanation(explanation)
```

Here we see that the second most probably class is hardly true, but is due to
the model picking up waxy areas of the produce and interpreting them as 
wax-light surface.

For text the explanation can be shown by highlighting the important words. It 
even includes a `shiny` application for interactively exploring text models:

![interactive text explainer](man/figures/shine_text_explanations.gif)

## Installation
`lime` is available on CRAN and can be installed using the standard approach:

```{r, eval=FALSE}
install.packages('lime')
```

To get the development version, install from GitHub instead:

```{r, eval=FALSE}
# install.packages('devtools')
devtools::install_github('thomasp85/lime')
```

## Code of Conduct
Please note that the 'lime' project is released with a
[Contributor Code of Conduct](https://lime.data-imaginist.com/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.

Owner

Name: Thomas Lin Pedersen
Login: thomasp85
Kind: user
Location: Copenhagen
Company: @posit-pbc, part of @tidyverse team

Website: www.data-imaginist.com
Twitter: thomasp85
Repositories: 121
Profile: https://github.com/thomasp85

Maker of tools focusing on data science and data visualisation

GitHub Events

Total

Watch event: 6

Last Year

Watch event: 6

Committers

Last synced: 11 months ago

All Time

Total Commits: 181
Total Committers: 16
Avg Commits per committer: 11.313
Development Distribution Score (DDS): 0.127

Past Year

Commits: 0
Committers: 0
Avg Commits per committer: 0.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Thomas Lin Pedersen	t**5@g**m	158
Michaël Benesty	p****e	7
nielsenmarkus11	n****1	2
Jeroen Ooms	j**s@g**m	2
millerjoey	a**0@g**m	1
Sam Lee	s**l@a**u	1
Philipp Kopper	4****r	1
Maëlle Salmon	m**n@y**e	1
Matt Dancho	m****4	1
Martin Jullum	j**m@n**o	1
Mara Averick	m**k@g**m	1
Ledger West	l**t@g**m	1
Jon Calder	j**r@g**m	1
Emil Hvitfeldt	e**t@g**m	1
Christoph Molnar	c**r@g**m	1
Chris Muir	C****r	1

Committer Domains (Top 20 + Academic)

nr.no: 1 alumni.caltech.edu: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time

Total issues: 86
Total pull requests: 15
Average time to close issues: 3 months
Average time to close pull requests: 5 months
Total issue authors: 70
Total pull request authors: 12
Average comments per issue: 2.44
Average comments per pull request: 0.93
Merged pull requests: 9
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

Make42 (5)
pkopper (3)
timcdlucas (3)
alanault (3)
mstaniak (3)
DiliSR (2)
nielsenmarkus11 (2)
thomasp85 (2)
ms1948 (2)
JLB9791 (1)
mirka-henninger (1)
kennysong (1)
hrampadarath (1)
ruizcrp (1)
sfd99 (1)

Pull Request Authors

nielsenmarkus11 (2)
pkopper (2)
jeroen (2)
NienkeVanTKlooster (1)
EmilHvitfeldt (1)
Ncalverley (1)
jmatias (1)
ChrisMuir (1)
samleegithub (1)
ledgerW (1)
tomazweiss (1)
talgalili (1)

Top Labels

Issue Labels

bug (1)

Pull Request Labels

Packages

Total packages: 3
Total downloads:
- cran 49,240 last-month
Total docker downloads: 36,199

Total dependent packages: 3
(may contain duplicates)
Total dependent repositories: 4
(may contain duplicates)
Total versions: 17
Total maintainers: 1

proxy.golang.org: github.com/thomasp85/lime

Documentation: https://pkg.go.dev/github.com/thomasp85/lime#section-documentation
License: other
Latest release: v0.5.3
published over 3 years ago

Versions: 4
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.4%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 6 months ago

cran.r-project.org: lime

Local Interpretable Model-Agnostic Explanations

Homepage: https://lime.data-imaginist.com
Documentation: http://cran.r-project.org/web/packages/lime/lime.pdf
License: MIT + file LICENSE
Latest release: 0.5.3
published over 3 years ago

Versions: 8
Dependent Packages: 3
Dependent Repositories: 3
Downloads: 49,240 Last month
Docker Downloads: 36,199

Rankings

Forks count: 0.6%

Docker downloads count: 0.6%

Stargazers count: 0.8%

Average: 6.3%

Downloads: 8.5%

Dependent packages count: 10.9%

Dependent repos count: 16.5%

Maintainers (1)

emilhhvitfeldt@gmail.com

Last synced: 6 months ago

conda-forge.org: r-lime

Homepage: https://github.com/thomasp85/lime
License: MIT
Latest release: 0.5.3
published over 3 years ago

Versions: 5
Dependent Packages: 0
Dependent Repositories: 1

Rankings

Forks count: 17.2%

Stargazers count: 17.9%

Dependent repos count: 24.3%

Average: 27.8%

Dependent packages count: 51.6%

Last synced: 6 months ago

Dependencies

DESCRIPTION cran

Matrix * imports
Rcpp * imports
assertthat * imports
ggplot2 * imports
glmnet * imports
gower * imports
grDevices * imports
methods * imports
stats * imports
stringi * imports
tools * imports
MASS * suggests
covr * suggests
h2o * suggests
htmlwidgets * suggests
keras * suggests
knitr * suggests
magick * suggests
mlr * suggests
ranger * suggests
rmarkdown * suggests
sessioninfo * suggests
shiny * suggests
shinythemes * suggests
testthat * suggests
text2vec * suggests
xgboost * suggests