broomstick

Convert decision tree objects into tidy data frames with broomstick.

The goal of broomstick is to extend the broom package to work with decision trees. It is currently borrowing heavily from the prototype package treezy, and will undergo much more development in the coming months.

Installation

You can install broomstick from github with:

# install.packages("remotes")
remotes::install_github("njtierney/broomstick")

Examples

rpart

library(rpart)
library(broomstick)
#> Loading required package: broom

fit_rpart <- rpart(Kyphosis ~ Age + Number + Start, 
                   data = kyphosis)

tidy(fit_rpart)
#> # A tibble: 3 x 2
#>   variable importance
#>   <fct>         <dbl>
#> 1 Start          8.20
#> 2 Age            3.10
#> 3 Number         1.52

gbm (Boosted Regression Tree)

library(gbm)
#> Loading required package: survival
#> 
#> Attaching package: 'survival'
#> The following object is masked from 'package:rpart':
#> 
#>     solder
#> Loading required package: lattice
#> Loading required package: splines
#> Loading required package: parallel
#> Loaded gbm 2.1.3
library(MASS)
fit_gbm <- gbm(calories ~., data = UScereal)
#> Distribution not specified, assuming gaussian ...

tidy(fit_gbm)
#> # A tibble: 10 x 2
#>    variable  importance
#>    <chr>          <dbl>
#>  1 potassium      62.5 
#>  2 fat            15.8 
#>  3 carbo           7.27
#>  4 fibre           5.26
#>  5 protein         5.23
#>  6 sugars          2.30
#>  7 sodium          1.69
#>  8 vitamins        0   
#>  9 shelf           0   
#> 10 mfr             0