| svmtrain {directlabels} | R Documentation |
False positive rates from several 1-SVM models
Description
Support Vector Machine density estimation (1-SVM) was applied to a set of negative control samples, and then used to test on a positive control.
Usage
data(svmtrain)
Format
A data frame with 378 observations on the following 5 variables.
replicatea factor with levels
123, the experimental replicate. We fit 1-SVM models to each replicate separately.ratea numeric vector, the percent of observations that were outside the trained model.
dataa factor with levels
KIF11testtrain, which set of observations did we measure. test and train are each 50% random splits of the negative controls in the experiment, and KIF11 is the positive control in the experiment.gammaa numeric vector, the tuning parameter of the radial basis function kernel.
nua numeric vector, the regularization parameter of the 1-SVM.