powered by
produces a plot of the svm solution along the path, and optinally indicates support points
# S3 method for svmpath plot(x, step, Size = 60, elbow.show = TRUE, support.show = TRUE, ...)
the svmpath object
svmpath
which step to plot; default is the last step. Use summary to see how many steps
summary
If the solution is non-linear, this is the gridsize for countour
countour
Should the points on the elbow be indicated
Should the support points be indicated
additional arguments to plot, allowing one to change, for example, "main", "xlab" etc
A list is returned silently, with the ingredients of the plot
A two-dimensional plot is produced of the SVM solution. Makes sense only if X is two-dimensional. If not, the first two dimensions will be used
The paper http://www-stat.stanford.edu/~hastie/Papers/svmpath.pdf, as well as the talk http://www-stat.stanford.edu/~hastie/TALKS/svmpathtalk.pdf.
coef.svmpath, svmpath, predict.svmpath, print.svmpath,summary.svmpath
# NOT RUN { data(svmpath) attach(balanced.overlap) fit <- svmpath(x,y,trace=TRUE,plot=FALSE) plot(fit,step=2) detach(2) # }
Run the code above in your browser using DataLab