Esempi in Python per KRR

Esempio n. 1

File: regression_krr_modular.py Progetto: memimo/shogun-liblinear

def krr_short ():
	print 'KRR_short'
	from shogun.Features import Labels, RealFeatures
	from shogun.Kernel import GaussianKernel
	from shogun.Regression import KRR

	width=0.8; tau=1e-6
	krr=KRR(tau, GaussianKernel(0, width), Labels(label_train))
	krr.train(RealFeatures(fm_train))
	out = krr.classify(RealFeatures(fm_test)).get_labels()
	return out

Esempio n. 2

def krr_short():
    print 'KRR_short'
    from shogun.Features import Labels, RealFeatures
    from shogun.Kernel import GaussianKernel
    from shogun.Regression import KRR

    width = 0.8
    tau = 1e-6
    krr = KRR(tau, GaussianKernel(0, width), Labels(label_train))
    krr.train(RealFeatures(fm_train))
    out = krr.apply(RealFeatures(fm_test)).get_labels()

    return krr, out

Esempio n. 3

File: regression_krr_modular.py Progetto: alesis/shogun

def regression_krr_modular (fm_train=traindat,fm_test=testdat,label_train=label_traindat,width=0.8,tau=1e-6):

	from shogun.Features import Labels, RealFeatures
	from shogun.Kernel import GaussianKernel
	from shogun.Regression import KRR

	feats_train=RealFeatures(fm_train)
	feats_test=RealFeatures(fm_test)

	kernel=GaussianKernel(feats_train, feats_train, width)

	labels=Labels(label_train)

	krr=KRR(tau, kernel, labels)
	krr.train(feats_train)

	kernel.init(feats_train, feats_test)
	out = krr.apply().get_labels()
	return out,kernel,krr

Esempio n. 4

File: regression_krr_modular.py Progetto: memimo/shogun-liblinear

def krr ():
	print 'KRR'
	from shogun.Features import Labels, RealFeatures
	from shogun.Kernel import GaussianKernel
	from shogun.Regression import KRR

	feats_train=RealFeatures(fm_train)
	feats_test=RealFeatures(fm_test)
	width=0.8
	kernel=GaussianKernel(feats_train, feats_train, width)

	tau=1e-6
	labels=Labels(label_train)

	krr=KRR(tau, kernel, labels)
	krr.train(feats_train)

	kernel.init(feats_train, feats_test)
	out = krr.classify().get_labels()
	return out

Esempio n. 5

def regression_krr_modular(fm_train=traindat,
                           fm_test=testdat,
                           label_train=label_traindat,
                           width=0.8,
                           tau=1e-6):

    from shogun.Features import Labels, RealFeatures
    from shogun.Kernel import GaussianKernel
    from shogun.Regression import KRR

    feats_train = RealFeatures(fm_train)
    feats_test = RealFeatures(fm_test)

    kernel = GaussianKernel(feats_train, feats_train, width)

    labels = Labels(label_train)

    krr = KRR(tau, kernel, labels)
    krr.train(feats_train)

    kernel.init(feats_train, feats_test)
    out = krr.apply().get_labels()
    return out, kernel, krr