From 31478d4d593185c09dcf0f4218eecc3fef9dd418 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Wed, 17 Sep 2014 11:22:31 +0100 Subject: [PATCH] improved docsting for optimize --- GPy/core/model.py | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/GPy/core/model.py b/GPy/core/model.py index 8c556da2..dc0a9f5e 100644 --- a/GPy/core/model.py +++ b/GPy/core/model.py @@ -213,6 +213,7 @@ class Model(Parameterized): def optimize(self, optimizer=None, start=None, **kwargs): """ Optimize the model using self.log_likelihood and self.log_likelihood_gradient, as well as self.priors. + kwargs are passed to the optimizer. They can be: :param max_f_eval: maximum number of function evaluations @@ -222,7 +223,15 @@ class Model(Parameterized): :param optimizer: which optimizer to use (defaults to self.preferred optimizer) :type optimizer: string - TODO: valid args + Valid optimizers are: + - 'scg': scaled conjugate gradient method, recommended for stability. + See also GPy.inference.optimization.scg + - 'fmin_tnc': truncated Newton method (see scipy.optimize.fmin_tnc) + - 'simplex': the Nelder-Mead simplex method (see scipy.optimize.fmin), + - 'lbfgsb': the l-bfgs-b method (see scipy.optimize.fmin_l_bfgs_b), + - 'sgd': stochastic gradient decsent (see scipy.optimize.sgd). For experts only! + + """ if self.is_fixed: raise RuntimeError, "Cannot optimize, when everything is fixed"