Exemplos de verify em Python

Exemplo n.º 1

Arquivo: neural_d_basic.py Projeto: yzy14800/520FinalProject

def testing(num):
    trainData = np.load("traindigitbasic.npy")
    trainLabels = samples.loadLabelsFile("data/digitdata/traininglabels", num)
    testData = np.load("testdigitbasic.npy")
    testLabels = samples.loadLabelsFile("data/digitdata/testlabels", 1000)
    validData = np.load("validationdigitbasic.npy")
    validLabels = samples.loadLabelsFile("data/digitdata/validationlabels", 1000)

    neural = NeuralNetworkClassifier(28 * 28, 50, 10, num, 3.5)
    neural.train(trainData[:, 0:num], trainLabels, 100)
    print "Test Data"
    guess = neural.classify(testData)
    samples.verify(neural, guess, testLabels)
    print "==================================="
    print "Validation Data"
    guess = neural.classify(validData)
    samples.verify(neural, guess, validLabels)

Exemplo n.º 2

def testing(num):
    trainData = np.load("traindigitbasic.npy")
    trainLabels = samples.loadLabelsFile("data/digitdata/traininglabels", num)
    testData = np.load("testdigitbasic.npy")
    testLabels = samples.loadLabelsFile("data/digitdata/testlabels", 1000)
    validData = np.load("validationdigitbasic.npy")
    validLabels = samples.loadLabelsFile("data/digitdata/validationlabels",
                                         1000)

    neural = NeuralNetworkClassifier(28 * 28, 50, 10, num, 3.5)
    neural.train(trainData[:, 0:num], trainLabels, 100)
    print "*************Test Data*************"
    guess = neural.classify(testData)
    samples.verify(neural, guess, testLabels)
    print "***********************************"
    print "************Valid Data*************"
    guess = neural.classify(validData)
    samples.verify(neural, guess, validLabels)

Exemplo n.º 3

def testing(num):
    trainData = samples.loadImagesFile("data/digitdata/trainingimages", num, 28, 28)
    trainLabels = samples.loadLabelsFile("data/digitdata/traininglabels", num)
    testData = samples.loadImagesFile("data/digitdata/testimages", 1000, 28, 28)
    testLabels = samples.loadLabelsFile("data/digitdata/testlabels", 1000)
    validData = samples.loadImagesFile("data/digitdata/validationimages", 1000, 28, 28)
    validLabels = samples.loadLabelsFile("data/digitdata/validationlabels", 1000)

    nb = NaiveBayesClassifier(1,0)
    nb.train(trainData, trainLabels)
    print "***********************************"
    print "*************Test Data*************"
    guess = nb.classify(testData)
    samples.verify(nb,guess,testLabels)
    print "***********************************"
    print "************Valid Data*************"
    guess=nb.classify(validData)
    samples.verify(nb,guess,validLabels)

Exemplo n.º 4

Arquivo: nb_f_basic.py Projeto: yzy14800/520FinalProject

def testing(num):
    trainData = samples.loadImagesFile("data/facedata/facedatatrain", num, 60, 70)
    trainLabels = samples.loadLabelsFile("data/facedata/facedatatrainlabels", num)
    testData = samples.loadImagesFile("data/facedata/facedatatest", 150, 60, 70)
    testLabels = samples.loadLabelsFile("data/facedata/facedatatestlabels", 151)
    validData = samples.loadImagesFile("data/facedata/facedatavalidation", 301, 60, 70)
    validLabels = samples.loadLabelsFile("data/facedata/facedatavalidationlabels", 301)

    nb = NaiveBayesClassifier(1, 0)
    nb.train(trainData, trainLabels)
    print "==================================="
    print "Test Data"
    guess = nb.classify(testData)
    samples.verify(nb, guess, testLabels)
    print "==================================="
    print "Validation Data"
    guess = nb.classify(validData)
    samples.verify(nb, guess, validLabels)

Exemplo n.º 5

Arquivo: nb_d_basic.py Projeto: yzy14800/520FinalProject

def testing(num):
    trainData = samples.loadImagesFile("data/digitdata/trainingimages", num, 28, 28)
    trainLabels = samples.loadLabelsFile("data/digitdata/traininglabels", num)
    testData = samples.loadImagesFile("data/digitdata/testimages", 1000, 28, 28)
    testLabels = samples.loadLabelsFile("data/digitdata/testlabels", 1000)
    validData = samples.loadImagesFile("data/digitdata/validationimages", 1000, 28, 28)
    validLabels = samples.loadLabelsFile("data/digitdata/validationlabels", 1000)

    nb = NaiveBayesClassifier(1,0)
    nb.train(trainData, trainLabels)
    print "==================================="
    print "Test Data"
    guess = nb.classify(testData)
    samples.verify(nb,guess,testLabels)
    print "==================================="
    print "Validation Data"
    guess=nb.classify(validData)
    samples.verify(nb,guess,validLabels)

Exemplo n.º 6

Arquivo: perceptron_f_basic.py Projeto: yzy14800/520FinalProject

def testing(num):
    trainData = samples.loadImagesFile("data/facedata/facedatatrain", num, 60, 70)
    trainLabels = samples.loadLabelsFile("data/facedata/facedatatrainlabels", num)
    testData = samples.loadImagesFile("data/facedata/facedatatest", 150, 60, 70)
    testLabels = samples.loadLabelsFile("data/facedata/facedatatestlabels", 151)
    validData = samples.loadImagesFile("data/facedata/facedatavalidation", 301, 60, 70)
    validLabels = samples.loadLabelsFile("data/facedata/facedatavalidationlabels", 301)

    perceptron=PerceptronClassifier(trainData, trainLabels,0)
    perceptron.train(trainData, trainLabels,10)
    print "==================================="
    print "Test Data"
    guess=perceptron.classify(testData)
    samples.verify(perceptron, guess, testLabels)
    print "==================================="
    print "Validation Data"
    guess=perceptron.classify(validData)
    samples.verify(perceptron,guess,validLabels)

Exemplo n.º 7

Arquivo: perceptronDigits.py Projeto: taotao-mars/AI-final-project

def testing(num):
    trainData = samples.loadImagesFile("data/digitdata/trainingimages", num, 28, 28)
    trainLabels = samples.loadLabelsFile("data/digitdata/traininglabels", num)
    testData = samples.loadImagesFile("data/digitdata/testimages", 1000, 28, 28)
    testLabels = samples.loadLabelsFile("data/digitdata/testlabels", 1000)
    validData = samples.loadImagesFile("data/digitdata/validationimages", 1000, 28, 28)
    validLabels = samples.loadLabelsFile("data/digitdata/validationlabels", 1000)

    perceptron=PerceptronClassifier(trainData, trainLabels,0)
    perceptron.train(trainData, trainLabels,10)
    print "***********************************"
    print "*************Test Data*************"
    guess=perceptron.classify(testData)
    samples.verify(perceptron, guess, testLabels)
    print "***********************************"
    print "************Valid Data*************"
    guess=perceptron.classify(validData)
    samples.verify(perceptron,guess,validLabels)

Exemplo n.º 8

Arquivo: perceptron_d_basic.py Projeto: yzy14800/520FinalProject

def testing(num):
    trainData = samples.loadImagesFile("data/digitdata/trainingimages", num, 28, 28)
    trainLabels = samples.loadLabelsFile("data/digitdata/traininglabels", num)
    testData = samples.loadImagesFile("data/digitdata/testimages", 1000, 28, 28)
    testLabels = samples.loadLabelsFile("data/digitdata/testlabels", 1000)
    validData = samples.loadImagesFile("data/digitdata/validationimages", 1000, 28, 28)
    validLabels = samples.loadLabelsFile("data/digitdata/validationlabels", 1000)

    perceptron=PerceptronClassifier(trainData, trainLabels,0)
    perceptron.train(trainData, trainLabels,10)
    print "==================================="
    print "Test Data"
    guess=perceptron.classify(testData)
    samples.verify(perceptron, guess, testLabels)
    print "==================================="
    print "Validation Data"
    guess=perceptron.classify(validData)
    samples.verify(perceptron,guess,validLabels)

Exemplo n.º 9

Arquivo: neural_f_basic.py Projeto: yzy14800/520FinalProject

def testing(num):
    trainData = np.load("trainfacebasic.npy")
    trainLabels = samples.loadLabelsFile("data/facedata/facedatatrainlabels", num)
    testData = np.load("testfacebasic.npy")
    testLabels = samples.loadLabelsFile("data/facedata/facedatatestlabels", 151)
    validData = np.load("validationfacebasic.npy")
    validLabels = samples.loadLabelsFile("data/facedata/facedatavalidationlabels", 301)
    loop=True
    while loop:
        neural = NeuralNetworkClassifier(60 * 70, 500, 1, num, 0.03)
        neural.train(trainData[:,0:num], trainLabels, 100)
        print "Test Data"
        guess = neural.classify(testData)
        loop=samples.verify(neural, guess, testLabels)
        if loop:
            continue
        print "==================================="
        print "Validation Data"
        guess = neural.classify(validData)
        samples.verify(neural, guess, validLabels)

Exemplo n.º 10

def testing(num):
    trainData = np.load("trainfaceadvanced.npy")
    trainLabels = samples.loadLabelsFile("data/facedata/facedatatrainlabels", num)
    testData = np.load("testfaceadvanced.npy")
    testLabels = samples.loadLabelsFile("data/facedata/facedatatestlabels", 151)
    validData = np.load("validationfaceadvanced.npy")
    validLabels = samples.loadLabelsFile("data/facedata/facedatavalidationlabels", 301)

    loop=True
    while loop:
        neural = NeuralNetworkClassifier(60 * (70+1), 500, 1, num, 0.03)
        neural.train(trainData[:,0:num], trainLabels, 100)
        print "Test Data"
        guess = neural.classify(testData)
        loop=samples.verify(neural, guess, testLabels)
        if loop:
            continue
        print "==================================="
        print "Validation Data"
        guess = neural.classify(validData)
        samples.verify(neural, guess, validLabels)

Exemplo n.º 11

def testing(num):
    trainData = samples.loadImagesFile("data/facedata/facedatatrain", num, 60,
                                       70)
    trainLabels = samples.loadLabelsFile("data/facedata/facedatatrainlabels",
                                         num)
    testData = samples.loadImagesFile("data/facedata/facedatatest", 150, 60,
                                      70)
    testLabels = samples.loadLabelsFile("data/facedata/facedatatestlabels",
                                        151)
    validData = samples.loadImagesFile("data/facedata/facedatavalidation", 301,
                                       60, 70)
    validLabels = samples.loadLabelsFile(
        "data/facedata/facedatavalidationlabels", 301)

    nb = NaiveBayesClassifier(1, 0)
    nb.train(trainData, trainLabels)
    print "***********************************"
    print "************Test Data**************"
    guess = nb.classify(testData)
    samples.verify(nb, guess, testLabels)
    print "***********************************"
    print "***********Valid Data**************"
    guess = nb.classify(validData)
    samples.verify(nb, guess, validLabels)

Exemplo n.º 12

def testing(num):
    trainData = samples.loadImagesFile("data/facedata/facedatatrain", num, 60,
                                       70)
    trainLabels = samples.loadLabelsFile("data/facedata/facedatatrainlabels",
                                         num)
    testData = samples.loadImagesFile("data/facedata/facedatatest", 150, 60,
                                      70)
    testLabels = samples.loadLabelsFile("data/facedata/facedatatestlabels",
                                        151)
    validData = samples.loadImagesFile("data/facedata/facedatavalidation", 301,
                                       60, 70)
    validLabels = samples.loadLabelsFile(
        "data/facedata/facedatavalidationlabels", 301)

    perceptron = PerceptronClassifier(trainData, trainLabels, 0)
    perceptron.train(trainData, trainLabels, 10)
    print "==================================="
    print "Test Data"
    guess = perceptron.classify(testData)
    samples.verify(perceptron, guess, testLabels)
    print "==================================="
    print "Validation Data"
    guess = perceptron.classify(validData)
    samples.verify(perceptron, guess, validLabels)