Thomas,
> thanks for your valuable comment. I assume that you used the function for
> regression - not classification.
I have been using it for classification and that is the issue. Looking
at ?lssvm, it has "regression is currently not supported" in the
details for the type argument.
Max
_
Dear Max,
thanks for your valuable comment. I assume that you used the function
for regression - not classification.
I use Mac OS X plattform (version 10.5.6). The R version is 2.8.1 (I
prefer to update to 2.9.1 not 2.9.0). The kernlab package version is
0.9-8.
The x and y-input into LSSVM
> To make things easier (using only two optimization parameters and not
> loosing performance) I wanted to use LS SVM regression (lssvm{kernlab}). But
> it looks to me that it is not yet implemented. At least I got error
> messages, which I could not find a solution for (Error in if (n !_dim(y)[1]
Dear R-community,
I was using SVM regression (svm {e1071}) for predictions of single
soil properties of a huge data set (3000 samples). There are for the
eps-regression using the radial basis kernel three optimization
parameters needed.
To make things easier (using only two optimization p
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