# \donttest{
# optimize an SVM with small costs on
# the 'iris' data set
r1 <- tunePareto(classifier = tunePareto.svm(),
data = iris[, -ncol(iris)],
labels = iris[, ncol(iris)],
cost=seq(0.01,0.1,0.01),
objectiveFunctions=list(cvWeightedError(10, 10),
cvSensitivity(10, 10, caseClass="setosa")))
print(r1)
# another call to tunePareto with higher costs
r2 <- tunePareto(classifier = tunePareto.svm(),
data = iris[, -ncol(iris)],
labels = iris[, ncol(iris)],
cost=seq(0.5,10,0.5),
objectiveFunctions=list(cvWeightedError(10, 10),
cvSensitivity(10, 10, caseClass="setosa")))
print(r2)
# merge the results
print(mergeTuneParetoResults(r1,r2))
# }
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