predict.gausspr {kernlab} | R Documentation |
Prediction of test data using Gaussian Processes
## S4 method for signature 'gausspr': predict(object, newdata, type = "response", coupler = "minpair")
object |
an S4 object of class gausspr created by the
gausspr function |
newdata |
a data frame or matrix containing new data |
type |
one of response , probabilities
indicating the type of output: predicted values or matrix of class
probabilities |
coupler |
Coupling method used in the multiclass case, can be one
of minpair or pkpd (see reference for more details). |
response |
predicted classes (the classes with majority vote) or the response value in regression. |
probabilities |
matrix of class probabilities (one column for each class and one row for each input). |
Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at
## example using the promotergene data set data(promotergene) ## create test and training set ind <- sample(1:dim(promotergene)[1],20) genetrain <- promotergene[-ind, ] genetest <- promotergene[ind, ] ## train a support vector machine gene <- gausspr(Class~.,data=genetrain,kernel="rbfdot",kpar=list(sigma=0.015)) gene ## predict gene type probabilities on the test set genetype <- predict(gene,genetest,type="probabilities") genetype