Hello all, I am trying to use the "svm" method provided by e1071 (Version: 1.5-16) together with a matrix provided by the SparseM package (Version: 0.73) but it fails with this message:> model <- svm(lm, lv, scale = TRUE, type = 'C-classification', kernel 'linear')Error in t.default(x) : argument is not a matrix although lm was created before with read.matrix.csr (from the e1071) package. I also tried to simply convert a normal matrix to a SparseM matrix and then pass it, but I get the same error again. According to the manual of svm(), this is supposed to work though: " x: a data matrix, a vector, or a sparse matrix (object of class 'matrix.csr' as provided by the package 'SparseM'). " Used R version: R version 2.4.0 Patched (2006-11-25 r39997) Does anyone know how I can use Sparse Matrices with e1071? This would be really important because the matrix is simply too large to write it out. Best regards, Chris -- Christian Holler System Administrator Chair of Prof. Dr. W.J. Paul Saarland University Germany Building E1 3, Room 3.20 phone: +49 - 681 / 302 - 5537 fax: +49 - 681 / 302 - 4290
Chris:
yes, this is indeed a bug (in predict.svm) - will be fixed in the next
release of e1071.
Thanks for pointing this out,
David
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Hello all,
I am trying to use the "svm" method provided by e1071 (Version:
1.5-16)
together with a matrix provided by the SparseM package (Version: 0.73)
but it fails with this message:
> > model <- svm(lm, lv, scale = TRUE, type =
'C-classification', kernel 'linear')
Error in t.default(x) : argument is not a matrix
although lm was created before with read.matrix.csr (from the e1071)
package.
I also tried to simply convert a normal matrix to a SparseM matrix and
then pass it, but I get the same error again.
According to the manual of svm(), this is supposed to work though:
" x: a data matrix, a vector, or a sparse matrix (object of class
'matrix.csr' as provided by the package 'SparseM').
"
Used R version: R version 2.4.0 Patched (2006-11-25 r39997)
Does anyone know how I can use Sparse Matrices with e1071? This would be
really important because the matrix is simply too large to write it out.
Best regards,
Chris