Make predictions from a "svmpath" object
Description
Provide a value for lambda
, and produce the fitted lagrange alpha
values. Provide values for x
, and get fitted function values or
class labels.
Usage
1 2 3 
Arguments
object 
fitted 
newx 
values of 
lambda 
the value of the regularization parameter. Note that

type 
type of prediction, with default 
... 
Generic compatibility 
Details
This implementation of the SVM uses a parameterization that is slightly
different but equivalent to the usual (Vapnik) SVM. Here
lambda=1/C.
The Lagrange multipliers are related via
αstar = alpha/lambda, where
alphastar is the usual multiplier, and
alpha our multiplier. Note that if alpha=0
, that
observation is right of the elbow; alpha=1
, left of the elbow;
0<alpha<1
on the elbow. The latter two cases are all support
points.
Value
In each case, the desired prediction.
Author(s)
Trevor Hastie
References
The paper http://wwwstat.stanford.edu/~hastie/Papers/svmpath.pdf, as well as the talk http://wwwstat.stanford.edu/~hastie/TALKS/svmpathtalk.pdf.
See Also
coef.svmpath, svmpath
Examples
1 2 3 4 5 6 