def performJob(): # construct Train & Test Data xTrain, yTrain, xTest, yTest = DatasetManipulator.getTrainAndTestData() # training the classifier classifier = ClassifierTrainer.trainClassifier(xTrain, yTrain) #predicting yPred = classifier.predict(xTest) #assessing the performance Validator.performValidation(yPred, yTest)
def testParameterPerformance(): startTime = time.time() allAlgorithmStartTime = startTime # define sizes trainDataSize = 10000 testDataSize = 100000 trainData,testData = utils.getDifferentTrainAndTestData(trainDataSize,testDataSize) #in order to assure that we have members form each class present testData = testData.append(dataReader.getSuffixDataFrame()) classifier = trainClassifierOnTrainingData(trainData=trainData) xTest,yTest = constructTestData(testData) yPred = classifier.predict(xTest) validator.performValidation(yPred, yTest) print("Total run time:{} s".format((time.time() - allAlgorithmStartTime)))