From 0c51239bddfcd2411b619d5790b290eded507c68 Mon Sep 17 00:00:00 2001
From: James Hensman <james.hensman@gmail.com>
Date: Fri, 24 Jan 2014 10:18:13 +0000
Subject: [PATCH] removed fitc_classification modle

---
 GPy/models/__init__.py            |  1 -
 GPy/models/fitc_classification.py | 47 -------------------------------
 2 files changed, 48 deletions(-)
 delete mode 100644 GPy/models/fitc_classification.py

diff --git a/GPy/models/__init__.py b/GPy/models/__init__.py
index 10ce577b..047658a4 100644
--- a/GPy/models/__init__.py
+++ b/GPy/models/__init__.py
@@ -6,7 +6,6 @@ from gp_classification import GPClassification
 from sparse_gp_regression import SparseGPRegression
 from svigp_regression import SVIGPRegression
 from sparse_gp_classification import SparseGPClassification
-from fitc_classification import FITCClassification
 from gplvm import GPLVM
 from bcgplvm import BCGPLVM
 from sparse_gplvm import SparseGPLVM
diff --git a/GPy/models/fitc_classification.py b/GPy/models/fitc_classification.py
deleted file mode 100644
index ee92a1b4..00000000
--- a/GPy/models/fitc_classification.py
+++ /dev/null
@@ -1,47 +0,0 @@
-# Copyright (c) 2013, Ricardo Andrade
-# Licensed under the BSD 3-clause license (see LICENSE.txt)
-
-
-import numpy as np
-from ..core import FITC
-from .. import likelihoods
-from .. import kern
-from ..likelihoods import likelihood
-
-class FITCClassification(FITC):
-    """
-    FITC approximation for classification
-
-    This is a thin wrapper around the FITC class, with a set of sensible defaults
-
-    :param X: input observations
-    :param Y: observed values
-    :param likelihood: a GPy likelihood, defaults to Binomial with probit link function
-    :param kernel: a GPy kernel, defaults to rbf+white
-    :param normalize_X:  whether to normalize the input data before computing (predictions will be in original scales)
-    :type normalize_X: False|True
-    :param normalize_Y:  whether to normalize the input data before computing (predictions will be in original scales)
-    :type normalize_Y: False|True
-    :rtype: model object
-
-    """
-
-    def __init__(self, X, Y=None, likelihood=None, kernel=None, normalize_X=False, normalize_Y=False, Z=None, num_inducing=10):
-        if kernel is None:
-            kernel = kern.rbf(X.shape[1]) + kern.white(X.shape[1],1e-3)
-
-        if likelihood is None:
-            noise_model = likelihoods.binomial()
-            likelihood = likelihoods.EP(Y, noise_model)
-        elif Y is not None:
-            if not all(Y.flatten() == likelihood.data.flatten()):
-                raise Warning, 'likelihood.data and Y are different.'
-
-        if Z is None:
-            i = np.random.permutation(X.shape[0])[:num_inducing]
-            Z = X[i].copy()
-        else:
-            assert Z.shape[1]==X.shape[1]
-
-        FITC.__init__(self, X, likelihood, kernel, Z=Z, normalize_X=normalize_X)
-        self.ensure_default_constraints()