def test_basic(self):
dataset = data_generators.linear1d_gaussian_noise()
k = GeneralizedLinearKernel()
clf = GPR(k)
clf.train(dataset)
y = clf.predict(dataset.samples)
assert_array_equal(y.shape, dataset.targets.shape)
def test_basic(self):
dataset = data_generators.linear1d_gaussian_noise()
k = GeneralizedLinearKernel()
clf = GPR(k)
clf.train(dataset)
y = clf.predict(dataset.samples)
assert_array_equal(y.shape, dataset.targets.shape)
def test_basic(self):
skip_if_no_external('scipy') # needed by GPR code
dataset = data_generators.linear1d_gaussian_noise()
k = GeneralizedLinearKernel()
clf = GPR(k)
clf.train(dataset)
y = clf.predict(dataset.samples)
assert_array_equal(y.shape, dataset.targets.shape)
def test_basic(self):
skip_if_no_external('scipy') # needed by GPR code
dataset = data_generators.linear1d_gaussian_noise()
k = GeneralizedLinearKernel()
clf = GPR(k)
clf.train(dataset)
y = clf.predict(dataset.samples)
assert_array_equal(y.shape, dataset.targets.shape)