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Change crescent data to optimize with .optimize()

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This commit is contained in:
Neil Lawrence 2015-07-19 11:27:16 +02:00
commit 7c8176e5fd
47 changed files with 30168 additions and 1116 deletions
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3
GPy/examples/classification.py
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@ -217,9 +217,8 @@ def crescent_data(model_type='Full', num_inducing=10, seed=default_seed, kernel=
elif model_type == 'FITC':
m = GPy.models.FITCClassification(data['X'], Y, kernel=kernel, num_inducing=num_inducing)
m['.*len'] = 3.
if optimize:
m.pseudo_EM()
m.optimize()
if plot:
m.plot()

6
GPy/examples/dimensionality_reduction.py
View file

@ -355,13 +355,13 @@ def ssgplvm_simulation(optimize=True, verbose=1,
Y = Ylist[0]
k = kern.Linear(Q, ARD=True) # + kern.white(Q, _np.exp(-2)) # + kern.bias(Q)
# k = kern.RBF(Q, ARD=True, lengthscale=10.)
m = SSGPLVM(Y, Q, init="pca", num_inducing=num_inducing, kernel=k)
m = SSGPLVM(Y, Q, init="rand", num_inducing=num_inducing, kernel=k, group_spike=True)
m.X.variance[:] = _np.random.uniform(0, .01, m.X.shape)
m.likelihood.variance = .1
m.likelihood.variance = .01
if optimize:
print("Optimizing model:")
m.optimize('scg', messages=verbose, max_iters=max_iters,
m.optimize('bfgs', messages=verbose, max_iters=max_iters,
gtol=.05)
if plot:
m.X.plot("SSGPLVM Latent Space 1D")