https://github.com/mlr-org/mlr3viz

Visualizations for mlr3
https://github.com/mlr-org/mlr3viz

ggplot2 mlr3 r r-package visualization visualizations

Last synced: about 23 hours ago
JSON representation

Visualizations for mlr3

• Host: GitHub
• URL: https://github.com/mlr-org/mlr3viz
• Owner: mlr-org
• License: lgpl-3.0
• Created: 2018-11-16T10:35:30.000Z (almost 6 years ago)
• Default Branch: main
• Last Pushed: 2024-11-06T16:25:59.000Z (about 23 hours ago)
• Last Synced: 2024-11-06T16:46:57.701Z (about 23 hours ago)
• Topics: ggplot2, mlr3, r, r-package, visualization, visualizations
• Language: R
• Homepage: https://mlr3viz.mlr-org.com
• Size: 226 MB
• Stars: 42
• Watchers: 13
• Forks: 8
• Open Issues: 26
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md
  • License: LICENSE

Awesome Lists containing this project

README

        
---

output: github_document

---

```{r, include = FALSE}

lgr::get_logger("mlr3")$set_threshold("warn")

knitr::opts_chunk$set(fig.path = "man/figures/README-")

knitr::opts_chunk$set(fig.path = "man/figures/README-")

set.seed(1)

options(

  datatable.print.nrows = 10,

  datatable.print.class = FALSE,

  datatable.print.keys = FALSE,

  width = 100)

# mute load messages

library("mlr3tuning")

```

# mlr3viz 

Package website: [release](https://mlr3viz.mlr-org.com/) | [dev](https://mlr3viz.mlr-org.com/dev/)

[![r-cmd-check](https://github.com/mlr-org/mlr3viz/actions/workflows/r-cmd-check.yml/badge.svg)](https://github.com/mlr-org/mlr3viz/actions/workflows/r-cmd-check.yml)

[![CRAN](https://www.r-pkg.org/badges/version/mlr3viz)](https://cran.r-project.org/package=mlr3viz)

[![StackOverflow](https://img.shields.io/badge/stackoverflow-mlr3-orange.svg)](https://stackoverflow.com/questions/tagged/mlr3)

[![Mattermost](https://img.shields.io/badge/chat-mattermost-orange.svg)](https://lmmisld-lmu-stats-slds.srv.mwn.de/mlr_invite/)

*mlr3viz* is the visualization package of the [mlr3](https://mlr-org.com/) ecosystem.

It features plots for mlr3 objects such as tasks, learners, predictions, benchmark results, tuning instances and filters via the `autoplot()` generic of [ggplot2](https://ggplot2.tidyverse.org/).

The package draws plots with the [viridis](https://CRAN.R-project.org/package=viridisLite) color palette and applies the [minimal theme](https://ggplot2.tidyverse.org/reference/ggtheme.html).

Visualizations include barplots, boxplots, histograms, ROC curves, and Precision-Recall curves.

The [gallery](https://mlr-org.com/gallery/technical/2022-12-22-mlr3viz/) features a **showcase post** of the plots in `mlr3viz`.

## Installation

Install the last release from CRAN:

```{r, eval = FALSE}

install.packages("mlr3")

```

Install the development version from GitHub:

```{r, eval = FALSE}

remotes::install_github("mlr-org/mlr3viz")

```

## Resources

The [gallery](https://mlr-org.com/gallery/technical/2022-12-22-mlr3viz/) features a showcase post of the visualization functions `mlr3viz`.

## Short Demo

```{r demo, message = FALSE, warning = FALSE, dpi=300}

library(mlr3)

library(mlr3viz)

task = tsk("pima")

learner = lrn("classif.rpart", predict_type = "prob")

rr = resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE)

# Default plot for task

autoplot(task, type = "target")

# ROC curve for resample result

autoplot(rr, type = "roc")

```

For more example plots you can have a look at the [pkgdown references](https://mlr3viz.mlr-org.com/reference/index.html) of the respective functions.