I got a regression model trained using the 'cubist' function of the
'Cubist' package. This works fine. I'm now searching for a graphical
representation of the regression model:
As the Cubist Algorithm is based on a forrest of trees (or a single tree
if 'committees==1'), is it somehow possible to a
):
[1] codetools_0.2-8 compiler_2.15.0 grid_2.15.0 iterators_1.0.6
[5] tools_2.15.0
-----
Thanks!
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Dominik Bruhn
mailto: domi...@dbruhn.de
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PLEASE do read
plotmo(m$finalModel)
---
which leads to this error:
Error in eval(expr, envir, enclos) : object 'Girth:Height' not found
Is this a bug or am I missing something?
Thanks!
On 09/06/12 18:09, Dominik Bruhn wrote:
> Max, thanks for your answer!
>> predict.train() w
ediction method does not work if the formula is changed.
Perhaps my question now got clearer.
Thanks again!
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PLEASE do read th
r, envir, enclos) : object 'Girth:Height' not found
---
How can I set the degree used when training a linear model without
changing the formula? I need the 'extractPrediction' functionallity.
Thanks!
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Dominik Bruhn
mailto: domi...@dbruhn.de
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Graduate Research Assistant
> Department of Computer Science
> University of Missouri-Columbia
> Columbia, MO 65211
> Cell: 573-825-8874
> Email : rc...@mail.missouri.edu
> http://home.ustc.edu.cn/~ahjxcrz
>
>
> -Original Message-
> From: Dominik Bruhn [mailto:domi
e.ustc.edu.cn/~ahjxcrz
>
>
> [[alternative HTML version deleted]]
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> and
ariance of the predictions is zero. caret uses the formula for
> R^2 by calculating the correlation between the observed data and the
> predictions which uses sd(pred) which is zero. I believe that the same
> would occur with other formulas for R^2.
>
> Max
>
> On Wed, May 16,
>> zero.
>>
>> Try using you own summary function (see ?trainControl) and put a
>> print(summary(data$pred)) in there to verify my claim.
>>
>> Max
>>
>> On Tue, May 15, 2012 at 5:55 AM, Dominik Bruhn wrote:
>>> Hy,
>>> I got the fo
in a divide by
>> zero.
>>
>> Try using you own summary function (see ?trainControl) and put a
>> print(summary(data$pred)) in there to verify my claim.
>>
>> Max
>>
>> On Tue, May 15, 2012 at 5:55 AM, Dominik Bruhn wrote:
>>> Hy,
>>>
working is 'LOOCV':
---
library(caret)
data(trees)
formula=Volume~Girth+Height
tc=trainControl(method='LOOCV')
train(formula, data=trees, method='rpart', trControl=tc)
---
Thanks!
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Dominik Bruhn
mailto: domi...@dbruhn.de
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