Python svm_sigmoidal_correction Examples

Example #1

File: test_ecoc_learner.py Project: zoe7791/milk

def test_ecoc_probability():
    features,labels = load()
    features = features[labels < 5]
    labels = labels[labels < 5]
    raw = svm.svm_raw(kernel=svm.dot_kernel(), C=1.)
    base = ctransforms(raw, svm.svm_sigmoidal_correction())
    learner = ecoc_learner(base, probability=True)
    model = learner.train(features[::2], labels[::2])
    results = list(map(model.apply, features[1::2]))
    results = np.array(results)
    assert results.shape[1] == len(set(labels))
    assert np.mean(results.argmax(1) == labels[1::2]) > .5

Example #2

File: test_svm.py Project: arnaudsj/milk

def test_platt_correction_class():
    F=numpy.ones(10)
    L=numpy.ones(10)
    F[:5] *= -1
    L[:5] *= 0
    corrector = svm_sigmoidal_correction()
    A,B = learn_sigmoid_constants(F,L)
    model = corrector.train(F,L)
    assert model.A == A
    assert model.B == B
    assert model.apply(10) > .99
    assert model.apply(-10) < .01

Example #3

File: test_svm.py Project: tzuryby/milk

def test_platt_correction_class():
    F = numpy.ones(10)
    L = numpy.ones(10)
    F[:5] *= -1
    L[:5] *= 0
    corrector = svm_sigmoidal_correction()
    A, B = learn_sigmoid_constants(F, L)
    model = corrector.train(F, L)
    assert model.A == A
    assert model.B == B
    assert model.apply(10) > .99
    assert model.apply(-10) < .01