AutoGAM is a wrapper package for mgcv that makes it
easier to create high-performing Generalized Additive Models (GAMs).
With its central function autogam(), by entering just a
dataset and the name of the outcome column as inputs, AutoGAM tries to
automate as much as possible the procedure of configuring a highly
accurate GAM at reasonably high speed, even for large datasets.
You can install the development version of autogam like so:
# install.packages("devtools")
devtools::install_github("tripartio/autogam")Here’s a simple example using the mtcars dataset to
predict mpg:
library(autogam)
autogam(mtcars, 'mpg')
#> Detecting distribution of `mpg`...
#> Loading required package: intervals
#>
#> Fitting GAM with `Inverse Gaussian` distribution...
#> ✔ GAM successfully fit with 86.1% standardized accuracy.
#>
#> Family: gaussian
#> Link function: inverse
#>
#> Formula:
#> mpg ~ cyl + s(disp, bs = "cr") + s(hp, bs = "cr") + s(drat, bs = "cr") +
#> s(wt, bs = "cr") + s(qsec, bs = "cr") + vs + am + gear +
#> s(carb, k = 3, bs = "cr")
#>
#> Estimated degrees of freedom:
#> 1.00 1.00 1.00 1.00 1.37 1.00 total = 11.37
#>
#> fREML score: 114.8354
#>
#> MAE: 1.307; Std. accuracy: 86.1%