def build(targetClassifierPath, classifierModule, featureSet, trainingPath, testPath, parameterByName):
# Save training
trainingDataset = sample_store.load(trainingPath)
trainingFeaturePath = classifierModule.saveSamples(trainingDataset, trainingDataset.getSampleIDs(), featureSet)
# Save test
testDataset = sample_store.load(testPath)
testFeaturePath = classifierModule.saveSamples(testDataset, testDataset.getSampleIDs(), featureSet)
# Train
return classifierModule.train(targetClassifierPath, trainingFeaturePath, testFeaturePath, parameterByName)
def getTestDataset(self):
return sample_store.load(self.information['windows']['test'])
def getTrainingDataset(self):
return sample_store.load(self.information['windows']['training'])
def getDataset(self):
return sample_store.load(self.information['dataset']['path'])
