Question

I’m using the caret library in R for model generation. I want to generate an earth (aka MARS) model and I want to specify the degree parameter for this model generation. According to the documentation (page 11) the earth method supports this parameter.

I get the following error message when specifying the parameter:

> library(caret)
> data(trees)
> train(Volume~Girth+Height, data=trees, method='earth', degree=1)
Error in { : 
  task 1 failed - "formal argument "degree" matched by multiple actual arguments"

How can I avoid this error when specifying the degree parameter?

> sessionInfo()
R version 2.15.0 (2012-03-30)
Platform: x86_64-pc-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=C                 LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] earth_3.2-3    plotrix_3.4    plotmo_1.3-1   leaps_2.9      caret_5.15-023
 [6] foreach_1.4.0  cluster_1.14.2 reshape_0.8.4  plyr_1.7.1     lattice_0.20-6

loaded via a namespace (and not attached):
[1] codetools_0.2-8 compiler_2.15.0 grid_2.15.0     iterators_1.0.6
[5] tools_2.15.0   

Answer 1

I found out how to do it, joran led me into the right direction:

Create a new function which generates the training grid. This function must accept the two parameters len and data. In order to retrieve the original training grid, you can call the createGrid method provided by the caret package. You can then modify the grid to your needs. For example to neave the nprune parameter unchanged and add degree from 1 to 5 use the following code:

  createMARSGrid <- function(len, data) {
      g = createGrid("earth", len, data)
      g = expand.grid(.nprune=g$.nprune, .degree=seq(1,5))
      return(g)
  }   

Then invoke it like this:

train(formula, data=data, method='earth', tuneGrid = createMARSGrid)