mergeTuneParetoResults: Calculate optimal solutions from several calls of tunePareto

In TunePareto: Multi-Objective Parameter Tuning for Classifiers

Calculate optimal solutions from several calls of tunePareto

Description

Merges the results of multiple TuneParetoResult objects as returned by tunePareto, and recalculates the optimal solutions for the merged solution set. All supplied TuneParetoResult objects must use the same objective functions.

Usage

mergeTuneParetoResults(...)

Arguments

...	A set of TuneParetoResult objects to be merged.

Value

A TuneParetoResult object containing the parameter configurations of all objects in the ... argument and selecting the Pareto-optimal solutions among all these configurations. For more details on the object structure, refer to tunePareto.

See Also

tunePareto, recalculateParetoSet

Examples

# 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))

TunePareto documentation built on Oct. 2, 2023, 5:06 p.m.