This function makes predictions from a crossvalidated sparsenet model,
using the stored "sparsenet.fit"
object, and the optimal value
chosen for lambda
.
1 2 3 4 
object 
Fitted 
newx 
Matrix of new values for 
which 
Either the paramaters of the minimum of the CV curves
(default 
... 
Not used. Other arguments to predict. 
This function makes it easier to use the results of crossvalidation to make a prediction.
The object returned depends the ... argument which is passed on
to the predict
method for sparsenet
objects.
Rahul Mazumder, Jerome Friedman and Trevor Hastie
Maintainer: Trevor Hastie <hastie@stanford.edu>
http://www.stanford.edu/~hastie/Papers/Sparsenet/jasa_MFH_final.pdf
glmnet
package, sparsenet
, cv.sparsenet
and
print
and plot
methods for both.
1 2 3 4  x=matrix(rnorm(100*20),100,20)
y=rnorm(100)
fitcv=cv.sparsenet(x,y)
predict(fitcv,x)

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