Python GaussianKernel.get_kernel_matrix Exemples

Exemple #1

Fichier : kernel_gaussian.py Projet : zym-wade/shogun

def kernel_gaussian(train_fname=traindat, test_fname=testdat, width=1.3):
    from shogun import RealFeatures, GaussianKernel, CSVFile

    feats_train = RealFeatures(CSVFile(train_fname))
    feats_test = RealFeatures(CSVFile(test_fname))

    kernel = GaussianKernel(feats_train, feats_train, width)
    km_train = kernel.get_kernel_matrix()

    kernel.init(feats_train, feats_test)
    km_test = kernel.get_kernel_matrix()
    return km_train, km_test, kernel

Exemple #2

Fichier : kernel_gaussian.py Projet : DEVESHTARASIA/shogun

def kernel_gaussian (train_fname=traindat,test_fname=testdat, width=1.3):
	from shogun import RealFeatures, GaussianKernel, CSVFile

	feats_train=RealFeatures(CSVFile(train_fname))
	feats_test=RealFeatures(CSVFile(test_fname))

	kernel=GaussianKernel(feats_train, feats_train, width)
	km_train=kernel.get_kernel_matrix()

	kernel.init(feats_train, feats_test)
	km_test=kernel.get_kernel_matrix()
	return km_train,km_test,kernel

Exemple #3

Fichier : kernel_sparse_gaussian.py Projet : zym-wade/shogun

def kernel_sparse_gaussian(fm_train_real=traindat,
                           fm_test_real=testdat,
                           width=1.1):
    from shogun import SparseRealFeatures
    from shogun import GaussianKernel

    feats_train = SparseRealFeatures(fm_train_real)
    feats_test = SparseRealFeatures(fm_test_real)

    kernel = GaussianKernel(feats_train, feats_train, width)
    km_train = kernel.get_kernel_matrix()

    kernel.init(feats_train, feats_test)
    km_test = kernel.get_kernel_matrix()
    return km_train, km_test, kernel

Exemple #4

Fichier : kernel_io.py Projet : zym-wade/shogun

def kernel_io(train_fname=traindat, test_fname=testdat, width=1.9):
    from shogun import RealFeatures, GaussianKernel, CSVFile
    from tempfile import NamedTemporaryFile

    feats_train = RealFeatures(CSVFile(train_fname))
    feats_test = RealFeatures(CSVFile(test_fname))

    kernel = GaussianKernel(feats_train, feats_train, width)
    km_train = kernel.get_kernel_matrix()
    tmp_train_csv = NamedTemporaryFile(suffix='train.csv')
    f = CSVFile(tmp_train_csv.name, "w")
    kernel.save(f)
    del f

    kernel.init(feats_train, feats_test)
    km_test = kernel.get_kernel_matrix()
    tmp_test_csv = NamedTemporaryFile(suffix='test.csv')
    f = CSVFile(tmp_test_csv.name, "w")
    kernel.save(f)
    del f

    return km_train, km_test, kernel

Exemple #5

Fichier : kernel_io.py Projet : DEVESHTARASIA/shogun

def kernel_io (train_fname=traindat,test_fname=testdat,width=1.9):
	from shogun import RealFeatures, GaussianKernel, CSVFile
	from tempfile import NamedTemporaryFile

	feats_train=RealFeatures(CSVFile(train_fname))
	feats_test=RealFeatures(CSVFile(test_fname))

	kernel=GaussianKernel(feats_train, feats_train, width)
	km_train=kernel.get_kernel_matrix()
	tmp_train_csv = NamedTemporaryFile(suffix='train.csv')
	f=CSVFile(tmp_train_csv.name, "w")
	kernel.save(f)
	del f

	kernel.init(feats_train, feats_test)
	km_test=kernel.get_kernel_matrix()
	tmp_test_csv = NamedTemporaryFile(suffix='test.csv')
	f=CSVFile(tmp_test_csv.name,"w")
	kernel.save(f)
	del f

	return km_train, km_test, kernel

Exemple #6

def classifier_gmnpsvm(fm_train_real, fm_test_real, label_train_multiclass, C):
    feats_train = RealFeatures(fm_train_real)
    feats_test = RealFeatures(fm_test_real)
    kernel = GaussianKernel(feats_train, feats_train, width)
    import time
    start = time.time()
    tmp = kernel.get_kernel_matrix()
    end = time.time()

    labels = MulticlassLabels(label_train_multiclass)

    svm = GMNPSVM(C, kernel, labels)
    svm.set_epsilon(epsilon)
    svm.parallel.set_num_threads(num_threads)
    svm.train(feats_train)

    out = svm.apply(feats_test).get_labels()
    return out