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Merge branch 'devel' of github.com:SheffieldML/GPy into devel

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Conflicts:
	GPy/examples/classification.py
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Ricardo 2013-09-20 15:55:48 +01:00
commit c129b98b3b
26 changed files with 316 additions and 177 deletions
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12
GPy/core/sparse_gp.py
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@ -16,16 +16,17 @@ class SparseGP(GPBase):
:type X: np.ndarray (num_data x input_dim)
:param likelihood: a likelihood instance, containing the observed data
:type likelihood: GPy.likelihood.(Gaussian | EP | Laplace)
:param kernel : the kernel (covariance function). See link kernels
:param kernel: the kernel (covariance function). See link kernels
:type kernel: a GPy.kern.kern instance
:param X_variance: The uncertainty in the measurements of X (Gaussian variance)
:type X_variance: np.ndarray (num_data x input_dim) | None
:param Z: inducing inputs (optional, see note)
:type Z: np.ndarray (num_inducing x input_dim) | None
:param num_inducing : Number of inducing points (optional, default 10. Ignored if Z is not None)
:param num_inducing: Number of inducing points (optional, default 10. Ignored if Z is not None)
:type num_inducing: int
:param normalize_(X|Y) : whether to normalize the data before computing (predictions will be in original scales)
:param normalize_(X|Y): whether to normalize the data before computing (predictions will be in original scales)
:type normalize_(X|Y): bool
"""
def __init__(self, X, likelihood, kernel, Z, X_variance=None, normalize_X=False):
@ -306,10 +307,11 @@ class SparseGP(GPBase):
def predict(self, Xnew, X_variance_new=None, which_parts='all', full_cov=False):
"""
Predict the function(s) at the new point(s) Xnew.
Arguments
---------
**Arguments**
:param Xnew: The points at which to make a prediction
:type Xnew: np.ndarray, Nnew x self.input_dim
:param X_variance_new: The uncertainty in the prediction points