predict.cv.glmnet: make predictions from a "cv.glmnet" object.
Description
This function makes predictions from a cross-validated glmnet model,
using the stored "glmnet.fit" object, and the optimal value
chosen for lambda.
Usage
## S3 method for class 'cv.glmnet':
predict(object, newx, s=c("lambda.1se","lambda.min"),...)
## S3 method for class 'cv.glmnet':
coef(object,s=c("lambda.1se","lambda.min"),...)
Arguments
object
Fitted "cv.glmnet" object.
newx
Matrix of new values for x at which predictions are
to be made. Must be a matrix; can be sparse as in Matrix
package. See documentation for predict.glmnet.
s
Value(s) of the penalty parameter lambda at which
predictions are required. Default is the value s="lambda.1se" stored
on the CV object. Alternatively s="lambda.min" can be
used. If s
...
Not used. Other arguments to predict.
Value
The object returned depends the ...argument which is passed on
to the predict method for glmnet objects.
Details
This function makes it easier to use the results of
cross-validation to make a prediction.
References
Friedman, J., Hastie, T. and Tibshirani, R. (2008)
Regularization Paths for Generalized Linear Models via Coordinate
Descent, Journal of Statistical Software, Vol. 33, Issue 1, Feb 2010http://www-stat.stanford.edu/~hastie/Papers/glmnet.pdfhttp://www.jstatsoft.org/v33/i01/
See Also
glmnet, and print, and coef methods, and cv.glmnet.