def runExperiment(self, classifier: Classifier, parameter: Parameter,
experimentPerformance: ExperimentPerformance,
crossValidation: CrossValidation, testSet: InstanceList):
for i in range(self.K):
trainSet = InstanceList(crossValidation.getTrainFold(i))
classifier.train(trainSet, parameter)
experimentPerformance.add(classifier.test(testSet))
def execute(self, experiment: Experiment) -> ExperimentPerformance:
"""
Execute the bootstrap run with the given classifier on the given data set using the given parameters.
PARAMETERS
----------
experiment : Experiment
Experiment to be run.
RETURNS
-------
ExperimentPerformance
An ExperimentPerformance instance.
"""
result = ExperimentPerformance()
for i in range(self.__numberOfBootstraps):
bootstrap = Bootstrap(experiment.getDataSet().getInstances(),
i + experiment.getParameter().getSeed())
bootstrapSample = InstanceList(bootstrap.getSample())
experiment.getClassifier().train(bootstrapSample,
experiment.getParameter())
result.add(experiment.getClassifier().test(
experiment.getDataSet().getInstanceList()))
return result