predict.ksvm: predict method for support vector object

In kernlab: Kernel-Based Machine Learning Lab

predict method for support vector object

Description

Prediction of test data using support vector machines

Usage

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

Arguments

object	an S4 object of class ksvm created by the ksvm function
newdata	a data frame or matrix containing new data
type	one of response, probabilities ,votes, decision indicating the type of output: predicted values, matrix of class probabilities, matrix of vote counts, or matrix of decision values.
coupler	Coupling method used in the multiclass case, can be one of minpair or pkpd (see reference for more details).

Value

If type(object) is C-svc, nu-svc, C-bsvm or spoc-svc the vector returned depends on the argument type:

response	predicted classes (the classes with majority vote).
probabilities	matrix of class probabilities (one column for each class and one row for each input).
votes	matrix of vote counts (one column for each class and one row for each new input)

If type(object) is eps-svr, eps-bsvr or nu-svr a vector of predicted values is returned. If type(object) is one-classification a vector of logical values is returned.

Author(s)

Alexandros Karatzoglou
[e-mail]

References

• T.F. Wu, C.J. Lin, R.C. Weng.
  Probability estimates for Multi-class Classification by Pairwise Coupling
  https://www.csie.ntu.edu.tw/~cjlin/papers/svmprob/svmprob.pdf

• H.T. Lin, C.J. Lin, R.C. Weng (2007), A note on Platt's probabilistic outputs for support vector machines. Machine Learning, 68, 267–276. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s10994-007-5018-6")}.

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 <- ksvm(Class~.,data=genetrain,kernel="rbfdot",
             kpar=list(sigma=0.015),C=70,cross=4,prob.model=TRUE)
gene

## predict gene type probabilities on the test set
genetype <- predict(gene,genetest,type="probabilities")
genetype

kernlab documentation built on Sept. 12, 2024, 6:51 a.m.