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License: GNU General Public License v2.0
Automatically exported from code.google.com/p/gcdnet
License: GNU General Public License v2.0
What steps will reproduce the problem?
1. Train logit model
2. Use predict with that model
What is the expected output? What do you see instead?
predict should return the predicted probability of the positive class.
Instead I get:
Error in as.matrix(as.matrix(cbind2(1, newx)) %*% nbeta) :
error in evaluating the argument 'x' in selecting a method for function 'as.matrix': Error in t(.Call(Csparse_dense_crossprod, y, t(x))) :
error in evaluating the argument 'x' in selecting a method for function 't': Error: Cholmod error 'X and/or Y have wrong dimensions' at file ../MatrixOps/cholmod_sdmult.c, line 90
What version of the product are you using? On what operating system?
I'm running gcdnet 1.0.1 and R 2.15.1 on Fedora 17.
Please provide any additional information below.
Using the Arcene dataset and executing the following code will give the above
error:
library(gcdnet)
arc <- read.csv("arcene.csv", header=FALSE)
fit <- gcdnet(arc[,-10001], arc[,10001], standardize=FALSE, method="logit")
pred <- rnorm(10000)
predict(fit, pred, type="link")
Original issue reported on code.google.com by [email protected]
on 16 Jul 2012 at 11:29
Attachments:
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