From 76eb36f13c850307619586c0107afed25b7750e9 Mon Sep 17 00:00:00 2001 From: Andreas Date: Fri, 14 Nov 2014 21:08:02 +0000 Subject: [PATCH] Small changes to 1vsAll --- GPy/models/one_vs_all_classification.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/GPy/models/one_vs_all_classification.py b/GPy/models/one_vs_all_classification.py index 76ea9406..2a0af892 100644 --- a/GPy/models/one_vs_all_classification.py +++ b/GPy/models/one_vs_all_classification.py @@ -2,11 +2,13 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) from ..core import GP +from . import SparseGPClassification from .. import likelihoods from .. import kern from ..inference.latent_function_inference.expectation_propagation import EP +import numpy as np -class OneVsAllClassification(GP): +class OneVsAllClassification(object): """ Gaussian Process classification: One vs all @@ -20,7 +22,7 @@ class OneVsAllClassification(GP): """ - def __init__(self, X, Y, kernel=None,Y_metadata=None): + def __init__(self, X, Y, kernel=None,Y_metadata=None,messages=True): if kernel is None: kernel = kern.RBF(X.shape[1]) @@ -36,6 +38,6 @@ class OneVsAllClassification(GP): Ynew[Y.flatten()!=yj] = 0 Ynew[Y.flatten()==yj] = 1 - m = GPy.models.GPClassification(X,Ynew,kernel=kernel,Y_metadata=Y_metadata,inference_method=inference_method) - m.optimize() + m = SparseGPClassification(X,Ynew,kernel=kernel,Y_metadata=Y_metadata) + m.optimize(messages=messages) self.results[yj] = m.predict(X)