predict method for Gaussian Processes object
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 |
newdata |
a data frame or matrix containing new data |
type |
one of |
coupler |
Coupling method used in the multiclass case, can be one
of |
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
C. K. I. Williams and D. Barber
Bayesian classification with Gaussian processes.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(12):1342-1351, 1998
http://www.dai.ed.ac.uk/homes/ckiw/postscript/pami_final.ps.gz
T.F. Wu, C.J. Lin, R.C. Weng.
Probability estimates for Multi-class Classification by
Pairwise Coupling
http://www.csie.ntu.edu.tw/~cjlin/papers/svmprob/svmprob.pdf
## 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")
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