From b55f84f04f6fd5bcbca27e854a77218db5cb3b84 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Mon, 11 May 2015 11:26:25 +0100 Subject: [PATCH] [predict] documentation --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 3acea54b..c2d2010c 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -236,7 +236,7 @@ class GP(Model): If full_cov and self.input_dim > 1, the return shape of var is Nnew x Nnew x self.input_dim. If self.input_dim == 1, the return shape is Nnew x Nnew. This is to allow for different normalizations of the output dimensions. - Note: If you want the predictive quantiles (e.g. 95% confidence interval) use :py:func:~GPy.core.gp.GP.predict_quantiles. + Note: If you want the predictive quantiles (e.g. 95% confidence interval) use :py:func:"~GPy.core.gp.GP.predict_quantiles". """ #predict the latent function values mu, var = self._raw_predict(Xnew, full_cov=full_cov, kern=kern)