https://github.com/njtierney/broomstick

:evergreen_tree: broom helpers for decision tree methods (rpart, randomForest, and more!) :evergreen_tree:
https://github.com/njtierney/broomstick

broom decision-trees gbm machine-learning randomforest rpart rstats statistical-learning

Last synced: about 2 months ago
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:evergreen_tree: broom helpers for decision tree methods (rpart, randomForest, and more!) :evergreen_tree:

• Host: GitHub
• URL: https://github.com/njtierney/broomstick
• Owner: njtierney
• License: other
• Created: 2017-08-23T13:27:12.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2023-12-03T06:27:24.000Z (10 months ago)
• Last Synced: 2024-06-12T18:28:49.490Z (3 months ago)
• Topics: broom, decision-trees, gbm, machine-learning, randomforest, rpart, rstats, statistical-learning
• Language: R
• Homepage: http://broomstick.njtierney.com/
• Size: 88.9 KB
• Stars: 28
• Watchers: 10
• Forks: 1
• Open Issues: 8
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE
  • Code of conduct: .github/CODE_OF_CONDUCT.md

Awesome Lists containing this project

README

        
---

output: github_document

---

```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "README-"

)

```

# broomstick

[![R build status](https://github.com/njtierney/broomstick/workflows/R-CMD-check/badge.svg)](https://github.com/njtierney/broomstick/actions)

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

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

Convert decision tree objects into tidy data frames with `broomstick`.

The goal of broomstick is to extend the [`broom`](https://github.com/tidyverse/broom) package to work with decision trees. It is currently borrowing heavily from the prototype package [`treezy`](https://github.com/njtierney/treezy).

## Installation

You can install broomstick from github with:

```{r gh-installation, eval = FALSE}

# install.packages("remotes")

remotes::install_github("njtierney/broomstick")

```

## Examples

## rpart

```{r example-rpart}

library(rpart)

library(broomstick)

fit_rpart <- rpart(Kyphosis ~ Age + Number + Start, 

                   data = kyphosis)

tidy(fit_rpart)

augment(fit_rpart)

```

## gbm (Boosted Regression Tree)

```{r example-gbm}

library(gbm)

library(MASS)

fit_gbm <- gbm(calories ~., data = UScereal)

tidy(fit_gbm)

```

## random forest

```{r example-rf}

library(randomForest)

ozone_rf <- randomForest(Ozone ~ ., 

                         data = airquality, 

                         importance = TRUE,

                         na.action = na.omit)

tidy(ozone_rf)

glance(ozone_rf)

augment(ozone_rf)

```