diff --git a/scikits/learn/ann/mlp.py b/scikits/learn/ann/mlp.py
index f1ad8b7fb4254c977e5086cc3ed911739168b012..b8449c5bce01da8290c34eea1f1864d9056ba8ad 100644
--- a/scikits/learn/ann/mlp.py
+++ b/scikits/learn/ann/mlp.py
@@ -118,7 +118,7 @@ class mlp:
         Returns:
             sum-squared-error over all data
         """
-        return N.sum(self.errfxn(self.wp,x,t))
+        return N.sum(self.errfxn(self.wp,x,t),axis=0)
 
 def main():
     """ Build/train/test MLP 
diff --git a/scikits/learn/ann/rbf.py b/scikits/learn/ann/rbf.py
index b3d692a1edb615a2adf9c2879b4bf475d1a779c1..0f5e5264cb585261cc7fc6f2650247b7b58a4cb9 100644
--- a/scikits/learn/ann/rbf.py
+++ b/scikits/learn/ann/rbf.py
@@ -86,7 +86,7 @@ class rbf:
         d_max = 0.0
         for i in self.centers:
             for j in self.centers:
-                tmp = N.sum(N.sqrt((i-j)**2))
+                tmp = N.sum(N.sqrt((i-j)**2),axis=0)
                 if tmp > d_max:
                     d_max = tmp
         self.variance = d_max/(2.0*len(X))
@@ -105,7 +105,7 @@ class rbf:
         Returns:
             sum-squared-error over all data
         """
-        return N.sum(self.err_fxn(self.wp,X,Y))
+        return N.sum(self.err_fxn(self.wp,X,Y),axis=0)
 
 def main():
     """ Build/train/test RBF net
diff --git a/scikits/learn/ann/srn.py b/scikits/learn/ann/srn.py
index 77ef6f28090d38d5a0f3713906fda821b96d5752..7def3d46258d752760b83bf68a995dcc88205e84 100644
--- a/scikits/learn/ann/srn.py
+++ b/scikits/learn/ann/srn.py
@@ -136,7 +136,7 @@ class srn:
         Returns:
             sum-squared-error over all data
         """
-        return N.sum(self.errfxn(self.wp,x,t))
+        return N.sum(self.errfxn(self.wp,x,t),axis=0)
                                                                                     
     
 def main():