predict.gausspr {kernlab}R Documentation

predict method for Gaussian Processes object

Description

Prediction of test data using Gaussian Processes

Usage

## S4 method for signature 'gausspr':
predict(object, newdata, type = "response", coupler = "minpair")

Arguments

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).

Value

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).

Author(s)

Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at

References

Examples


## 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

[Package kernlab version 0.9-8 Index]