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)))
