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'])