From bb0aed4596444cba2194e0e9bc578980cfccc783 Mon Sep 17 00:00:00 2001
From: Raghav R V <ragvrv@gmail.com>
Date: Tue, 30 Jun 2015 16:15:17 +0530
Subject: [PATCH 1/2] FIX use best_estimator_ as delegate to avoid incorrect
 attr checks

---
 sklearn/grid_search.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/sklearn/grid_search.py b/sklearn/grid_search.py
index 07bf443eb9c95..7fa8fed79958d 100644
--- a/sklearn/grid_search.py
+++ b/sklearn/grid_search.py
@@ -415,7 +415,7 @@ def score(self, X, y=None):
                           ChangedBehaviorWarning)
         return self.scorer_(self.best_estimator_, X, y)
 
-    @if_delegate_has_method(delegate='estimator')
+    @if_delegate_has_method(delegate='best_estimator_')
     def predict(self, X):
         """Call predict on the estimator with the best found parameters.
 
@@ -431,7 +431,7 @@ def predict(self, X):
         """
         return self.best_estimator_.predict(X)
 
-    @if_delegate_has_method(delegate='estimator')
+    @if_delegate_has_method(delegate='best_estimator_')
     def predict_proba(self, X):
         """Call predict_proba on the estimator with the best found parameters.
 
@@ -447,7 +447,7 @@ def predict_proba(self, X):
         """
         return self.best_estimator_.predict_proba(X)
 
-    @if_delegate_has_method(delegate='estimator')
+    @if_delegate_has_method(delegate='best_estimator_')
     def predict_log_proba(self, X):
         """Call predict_log_proba on the estimator with the best found parameters.
 
@@ -463,7 +463,7 @@ def predict_log_proba(self, X):
         """
         return self.best_estimator_.predict_log_proba(X)
 
-    @if_delegate_has_method(delegate='estimator')
+    @if_delegate_has_method(delegate='best_estimator_')
     def decision_function(self, X):
         """Call decision_function on the estimator with the best found parameters.
 
@@ -479,7 +479,7 @@ def decision_function(self, X):
         """
         return self.best_estimator_.decision_function(X)
 
-    @if_delegate_has_method(delegate='estimator')
+    @if_delegate_has_method(delegate='best_estimator_')
     def transform(self, X):
         """Call transform on the estimator with the best found parameters.
 
@@ -495,7 +495,7 @@ def transform(self, X):
         """
         return self.best_estimator_.transform(X)
 
-    @if_delegate_has_method(delegate='estimator')
+    @if_delegate_has_method(delegate='best_estimator_')
     def inverse_transform(self, Xt):
         """Call inverse_transform on the estimator with the best found parameters.
 

From 9533a814809f51e3685463850331e4c4f91fd602 Mon Sep 17 00:00:00 2001
From: Raghav R V <ragvrv@gmail.com>
Date: Tue, 30 Jun 2015 16:20:48 +0530
Subject: [PATCH 2/2] FIX raise NotFittedError before checking if model
 supports predict_proba

---
 sklearn/svm/base.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/sklearn/svm/base.py b/sklearn/svm/base.py
index 6bbb4879d5166..df14e61f87678 100644
--- a/sklearn/svm/base.py
+++ b/sklearn/svm/base.py
@@ -571,6 +571,7 @@ def predict(self, X):
     # probabilities are not available depending on a setting, introduce two
     # estimators.
     def _check_proba(self):
+        check_is_fitted(self, 'support_')
         if not self.probability or self.probA_.size == 0 or self.probB_.size == 0:
             raise AttributeError("predict_proba is not available when fitted with"
                                  " probability=False")