predict.gcdnet {gcdnet} | R Documentation |
Similar to other predict methods, this functions predicts fitted values and class labels from a fitted gcdnet
object.
## S3 method for class 'gcdnet' predict(object, newx, s = NULL, type=c("class","link"), ...)
object |
fitted |
newx |
matrix of new values for |
s |
value(s) of the penalty parameter |
type |
type of prediction required.
|
... |
Not used. Other arguments to predict. |
s
is the new vector at which predictions are requested. If s
is not in the lambda sequence used for fitting the model, the predict
function will use linear interpolation to make predictions. The new values are interpolated using a fraction of predicted values from both left and right lambda
indices.
The object returned depends on type.
Yi Yang, Yuwen Gu and Hui Zou
Maintainer: Yi Yang <yi.yang6@mcgill.ca>
Yang, Y. and Zou, H. (2012), "An Efficient Algorithm for Computing The HHSVM and Its Generalizations," Journal of Computational and Graphical Statistics, 22, 396-415.
BugReport: https://github.com/emeryyi/fastcox.git
Friedman, J., Hastie, T., and Tibshirani, R. (2010), "Regularization paths for generalized
linear models via coordinate descent," Journal of Statistical Software, 33, 1.
http://www.jstatsoft.org/v33/i01/
coef
method
data(FHT) m1 = gcdnet(x=FHT$x,y=FHT$y) print(predict(m1,type="class",newx=FHT$x[2:5,]))