Python TrainerValidator.plotResults Beispiele

Beispiel #1

Datei: model_evaluation.py Projekt: quentinms/PCML---Mini-Project

	def createMLPsP(self, H1, H2, nu, batchsize, k):
		
		for j in range(4,8) :
			data = Data(k, 0, 0)
			data.importDataFromMat()
			data.normalize()
			train = TrainerValidator(k, 50, H1, H2, nu, j/10.0, batchsize, data)
			train.trainAndClassify()
			train.plotResults()

Beispiel #2

Datei: model_evaluation.py Projekt: quentinms/PCML---Mini-Project

	def createMLPsH(self, H1, nu, mu, batchsize, k):
		
		for j in range(10) :
			data = Data(k, 0, 0)
			data.importDataFromMat()
			data.normalize()
			train = TrainerValidator(k, 5, H1, (j+1)*10, nu, mu, batchsize, data)
			train.trainAndClassify()
			train.plotResults()

Beispiel #3

Datei: main.py Projekt: quentinms/PCML---Mini-Project

def testBinary():
    k = 2

    data = Data(k, 0, 0)
    data.importDataFromMat()
    data.normalize()

    train = TrainerValidator(k, 70, 100, 10, 0.1, 0.2, 1, data)
    train.trainAndClassify()
    train.plotResults()

    test = Test(train.getMLP(), data, k)
    test.classify()
    test.examples()
    test.plot_confusion_matrix()