Esempi in Python per MPDSVM

Esempio n. 1

def classifier_mpdsvm_modular(fm_train_real=traindat,
                              fm_test_real=testdat,
                              label_train_twoclass=label_traindat,
                              C=1,
                              epsilon=1e-5):

    from shogun.Features import RealFeatures, BinaryLabels
    from shogun.Kernel import GaussianKernel
    from shogun.Classifier import MPDSVM

    feats_train = RealFeatures(fm_train_real)
    feats_test = RealFeatures(fm_test_real)
    width = 2.1
    kernel = GaussianKernel(feats_train, feats_train, width)

    labels = BinaryLabels(label_train_twoclass)

    svm = MPDSVM(C, kernel, labels)
    svm.set_epsilon(epsilon)
    svm.train()

    kernel.init(feats_train, feats_test)
    svm.apply().get_labels()
    predictions = svm.apply()
    return predictions, svm, predictions.get_labels()

Esempio n. 2

File: classifier_mpdsvm_modular.py Progetto: AlexBinder/shogun

def classifier_mpdsvm_modular (fm_train_real=traindat,fm_test_real=testdat,label_train_twoclass=label_traindat,C=1,epsilon=1e-5):

	from shogun.Features import RealFeatures, BinaryLabels
	from shogun.Kernel import GaussianKernel
	from shogun.Classifier import MPDSVM

	feats_train=RealFeatures(fm_train_real)
	feats_test=RealFeatures(fm_test_real)
	width=2.1
	kernel=GaussianKernel(feats_train, feats_train, width)

	labels=BinaryLabels(label_train_twoclass)

	svm=MPDSVM(C, kernel, labels)
	svm.set_epsilon(epsilon)
	svm.train()

	kernel.init(feats_train, feats_test)
	svm.apply().get_labels()
	predictions = svm.apply()
	return predictions, svm, predictions.get_labels()

Esempio n. 3

File: classifier_mpdsvm_modular.py Progetto: polyactis/test

def mpdsvm ():
	print 'MPDSVM'

	from shogun.Features import RealFeatures, Labels
	from shogun.Kernel import GaussianKernel
	from shogun.Classifier import MPDSVM

	feats_train=RealFeatures(fm_train_real)
	feats_test=RealFeatures(fm_test_real)
	width=2.1
	kernel=GaussianKernel(feats_train, feats_train, width)

	C=1
	epsilon=1e-5
	labels=Labels(label_train_twoclass)

	svm=MPDSVM(C, kernel, labels)
	svm.set_epsilon(epsilon)
	svm.train()

	kernel.init(feats_train, feats_test)
	svm.classify().get_labels()