Hi,
I am trying to do multinomial regression using the glmnet package, but the
following gives me an error (for no reason apparent to me):
library(glmnet)
cv.glmnet(x=matrix(c(1,2,3,4,5,6,1,2,3,4,5,6),
nrow=6),y=as.factor(c(1,2,1,2,3,3)),family='multinomial',alpha=0.5,
nfolds=2)
The error i get is:
Error in if (outlist$msg != "Unknown error") return(outlist) :
argument is of length zero
If i change the number of folds to 1, i get a seg fault:
*** caught segfault ***
address 0x0, cause 'memory not mapped'
Traceback:
1: .Fortran("lognet", parm = alpha, nobs, nvars, nc, as.double(x),
y,
offset, jd, vp, ne, nx, nlam, flmin, ulam, thresh, isd, maxit, kopt, lmu
= integer(1), a0 = double(nlam * nc), ca = double(nx * nlam * nc),
ia = integer(nx), nin = integer(nlam), nulldev = double(1), dev
double(nlam), alm = double(nlam), nlp = integer(1), jerr = integer(1),
PACKAGE = "glmnet")
2: lognet(x, is.sparse, ix, jx, y, weights, offset, type, alpha, nobs,
nvars, jd, vp, ne, nx, nlam, flmin, ulam, thresh, isd, vnames, maxit,
HessianExact, family)
3: glmnet(x[!which, ], y_sub, lambda = lambda, offset = offset_sub,
weights = weights[!which], ...)
4: cv.glmnet(x = matrix(c(1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6), nrow 6), y =
as.factor(c(1, 2, 1, 2, 3, 3)), family = "multinomial",
alpha = 0.5, nfolds = 1)
Possible actions:
any ideas?
Brian.
[[alternative HTML version deleted]]
On 2011-02-17 13:45, Brian Tsai wrote:> Hi, > > I am trying to do multinomial regression using the glmnet package, but the > following gives me an error (for no reason apparent to me): > > library(glmnet) > cv.glmnet(x=matrix(c(1,2,3,4,5,6,1,2,3,4,5,6), > nrow=6),y=as.factor(c(1,2,1,2,3,3)),family='multinomial',alpha=0.5, > nfolds=2) > > The error i get is: > Error in if (outlist$msg != "Unknown error") return(outlist) : > argument is of length zero > > > If i change the number of folds to 1, i get a seg fault: > *** caught segfault *** > address 0x0, cause 'memory not mapped' > > Traceback: > 1: .Fortran("lognet", parm = alpha, nobs, nvars, nc, as.double(x), y, > offset, jd, vp, ne, nx, nlam, flmin, ulam, thresh, isd, maxit, kopt, lmu > = integer(1), a0 = double(nlam * nc), ca = double(nx * nlam * nc), > ia = integer(nx), nin = integer(nlam), nulldev = double(1), dev > double(nlam), alm = double(nlam), nlp = integer(1), jerr = integer(1), > PACKAGE = "glmnet") > 2: lognet(x, is.sparse, ix, jx, y, weights, offset, type, alpha, nobs, > nvars, jd, vp, ne, nx, nlam, flmin, ulam, thresh, isd, vnames, maxit, > HessianExact, family) > 3: glmnet(x[!which, ], y_sub, lambda = lambda, offset = offset_sub, > weights = weights[!which], ...) > 4: cv.glmnet(x = matrix(c(1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6), nrow > 6), y = as.factor(c(1, 2, 1, 2, 3, 3)), family = "multinomial", > alpha = 0.5, nfolds = 1) > > Possible actions:Update glmnet? What version are you using? With glmnet 1.5.2, I just get a message reminding me that "nfolds must be bigger than 3; nfolds=10 recommended". Peter Ehlers> > > > any ideas? > > > Brian. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.