apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-10 04:22:38 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

minor adjustments

Browse source
This commit is contained in:
Max Zwiessele 2013-06-28 11:13:20 +01:00
parent 96829862cc
commit a8eb7eb5f7
2 changed files with 4 additions and 4 deletions
Download patch file Download diff file Expand all files Collapse all files

7
GPy/examples/dimensionality_reduction.py
View file

@ -254,7 +254,7 @@ def bgplvm_simulation(optimize='scg',
Y = Ylist[0]
k = kern.linear(Q, ARD=True) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2)) # + kern.bias(Q)
m = BayesianGPLVM(Y, Q, init="PCA", num_inducing=num_inducing, kernel=k, _debug=True)
m = BayesianGPLVM(Y, Q, init="PCA", num_inducing=num_inducing, kernel=k)
# m.constrain('variance|noise', logexp_clipped())
m['noise'] = Y.var() / 100.
@ -279,11 +279,12 @@ def mrd_simulation(optimize=True, plot=True, plot_sim=True, **kw):
reload(mrd); reload(kern)
k = kern.linear(Q, [.05] * Q, ARD=True) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2))
k = kern.linear(Q, ARD=True) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2))
m = mrd.MRD(Ylist, input_dim=Q, num_inducing=num_inducing, kernels=k, initx="", initz='permute', **kw)
m.ensure_default_constraints()
for i, Y in enumerate(Ylist):
m['{}_noise'.format(i + 1)] = Y.var() / 100.
m['{}_noise'.format(i)] = Y.var() / 100.
# DEBUG