mirror of
https://github.com/SheffieldML/GPy.git
synced 2026-04-25 04:46:23 +02:00
29 lines
960 B
Python
29 lines
960 B
Python
# Copyright (c) 2013, the GPy Authors (see AUTHORS.txt)
|
|
# Licensed under the BSD 3-clause license (see LICENSE.txt)
|
|
|
|
from ..core import GP
|
|
from .. import likelihoods
|
|
from .. import kern
|
|
from ..inference.latent_function_inference.expectation_propagation import EP
|
|
|
|
class GPClassification(GP):
|
|
"""
|
|
Gaussian Process classification
|
|
|
|
This is a thin wrapper around the models.GP class, with a set of sensible defaults
|
|
|
|
:param X: input observations
|
|
:param Y: observed values, can be None if likelihood is not None
|
|
:param kernel: a GPy kernel, defaults to rbf
|
|
|
|
.. Note:: Multiple independent outputs are allowed using columns of Y
|
|
|
|
"""
|
|
|
|
def __init__(self, X, Y, kernel=None,Y_metadata=None):
|
|
if kernel is None:
|
|
kernel = kern.RBF(X.shape[1])
|
|
|
|
likelihood = likelihoods.Bernoulli()
|
|
|
|
GP.__init__(self, X=X, Y=Y, kernel=kernel, likelihood=likelihood, inference_method=EP(), name='gp_classification')
|