From e58cc51c4704438b096a0cf519e67e0bde10b4d6 Mon Sep 17 00:00:00 2001 From: javiergonzalezh Date: Mon, 15 Jun 2015 18:42:29 +0100 Subject: [PATCH] allowing set initial noise variance for GPRegression --- GPy/models/gp_regression.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/GPy/models/gp_regression.py b/GPy/models/gp_regression.py index 7b8fb63f..105a63e7 100644 --- a/GPy/models/gp_regression.py +++ b/GPy/models/gp_regression.py @@ -16,6 +16,7 @@ class GPRegression(GP): :param Y: observed values :param kernel: a GPy kernel, defaults to rbf :param Norm normalizer: [False] + :param noise_var: the noise variance for Gaussian likelhood, defaults to 1. Normalize Y with the norm given. If normalizer is False, no normalization will be done @@ -25,12 +26,12 @@ class GPRegression(GP): """ - def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None): + def __init__(self, X, Y, kernel=None, Y_metadata=None, normalizer=None, noise_var=1.): if kernel is None: kernel = kern.RBF(X.shape[1]) - - likelihood = likelihoods.Gaussian() + + likelihood = likelihoods.Gaussian(variance=noise_var) super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='GP regression', Y_metadata=Y_metadata, normalizer=normalizer)