- Modified BLDA, SWLDA:

  - Added predict_proba
 On branch master
 Your branch is up to date with 'origin/master'.

 Changes to be committed:
	modified:   baseline/erp/blda.py
	modified:   baseline/erp/swlda.py

baseline/erp/blda.py

@@ -98,12 +98,11 @@ def decision_function(self,X):
         return np.dot(X.T, self.w) 
 
     def predict(self, X, y=None):
-        return self.decision_function(X)
-
+        return self.decision_function(X)            
 
     def score(self,X, y=None):
         pass
 
-    def predict_proba(self,X):
-        pass
+    def predict_proba(self, X):
+        return self.decision_function(X)
 

baseline/erp/swlda.py

@@ -4,6 +4,7 @@
 from sklearn.metrics import accuracy_score
 from sklearn.utils.extmath import softmax
 from .stepwise.stepwise import stepwisefit
+from copy import deepcopy
 import numpy as np
 
 class SWLDA(BaseEstimator, ClassifierMixin): 
@@ -43,4 +44,5 @@ def score(self,X, y=None):
         return accuracy_score(y, self.predict(X))
 
     def predict_proba(self,X):
-        return softmax(self.decision_function(X))
+        # return softmax(self.decision_function(X))
+        return self.decision_function(X)