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Added sparseGPLVM_oil example

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Andreas 2013-07-15 19:35:52 +01:00
parent ffd87898e6
commit 63bf417e99
1 changed files with 22 additions and 0 deletions
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22
GPy/examples/dimensionality_reduction.py
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@ -60,6 +60,28 @@ def GPLVM_oil_100(optimize=True):
m.plot_latent(labels=m.data_labels) m.plot_latent(labels=m.data_labels)
return m return m
def sparseGPLVM_oil(optimize=True, N=100, Q=6, num_inducing=15, max_iters=50):
np.random.seed(0)
data = GPy.util.datasets.oil()
Y = data['X'][:N]
Y = Y - Y.mean(0)
Y /= Y.std(0)
# create simple GP model
kernel = GPy.kern.rbf(Q, ARD=True) + GPy.kern.bias(Q)
m = GPy.models.SparseGPLVM(Y, Q, kernel=kernel, num_inducing = num_inducing)
m.data_labels = data['Y'].argmax(axis=1)
# optimize
if optimize:
m.optimize('scg', messages=1, max_iters = max_iters)
# plot
print(m)
#m.plot_latent(labels=m.data_labels)
return m
def swiss_roll(optimize=True, N=1000, num_inducing=15, Q=4, sigma=.2, plot=False): def swiss_roll(optimize=True, N=1000, num_inducing=15, Q=4, sigma=.2, plot=False):
from GPy.util.datasets import swiss_roll_generated from GPy.util.datasets import swiss_roll_generated
from GPy.core.transformations import logexp_clipped from GPy.core.transformations import logexp_clipped