[R] caret: compare linear models of different degree

[Dominik Bruhn]

The same statement is true for the "plotmo" function. It also does not
handle the situations right if the training functions contains
interactions. You can try this out using this code:

----
library(caret)
data(trees)
m = train(Volume~(Girth+Height)^2, data=trees, method="lm")
plotmo(m$finalModel)
---

which leads to this error:
----
Error in eval(expr, envir, enclos) : object 'Girth:Height' not found
----

Is this a bug or am I missing something?

Thanks!

On 09/06/12 18:09, Dominik Bruhn wrote:
> Max, thanks for your answer!
>> predict.train() will handle the formulas. If you want to compare the
>> models in terms of their predictive performance, set the seeds prior
>> to running the model. This will ensure that the same resampling
>> indices are used in train(). If you do this, the resamples() function
>> can be used to make formal comparisons between the models:
> 
> I think I did not express my question in the right way: I want to use
> the extractPrediction function because I want to plot some stats using
> the plotObsVsPred method. As stated in my previous mail, the
> extractPrediction method does not work if the formula is changed.
> 
> Perhaps my question now got clearer.
> 
> Thanks again!
> 


-- 
Dominik Bruhn
mailto: dominik at dbruhn.de