From 30262a84225ad3d7dd3476cef98b12bfffe4530f Mon Sep 17 00:00:00 2001
From: Joel Lowery <joeltlowery@gmail.com>
Date: Fri, 14 Apr 2017 00:11:40 -0500
Subject: [PATCH] Fix output of linearRegCostFunction

---
 ex5/ex5.py                   | 2 +-
 ex5/linearRegCostFunction.py | 2 ++
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/ex5/ex5.py b/ex5/ex5.py
index 23318ab..afcde38 100644
--- a/ex5/ex5.py
+++ b/ex5/ex5.py
@@ -61,7 +61,7 @@
 #  regression.
 
 theta = np.array([1, 1])
-J = linearRegCostFunction(np.column_stack((np.ones(m), X)), y, theta, Lambda=1)[0]
+J, _ = linearRegCostFunction(np.column_stack((np.ones(m), X)), y, theta, Lambda=1)
 
 print('Cost at theta = [1  1]: %f \n(this value should be about 303.993192)\n' % J)
 
diff --git a/ex5/linearRegCostFunction.py b/ex5/linearRegCostFunction.py
index d87ebc7..02730a7 100644
--- a/ex5/linearRegCostFunction.py
+++ b/ex5/linearRegCostFunction.py
@@ -8,6 +8,8 @@ def linearRegCostFunction(X, y, theta, Lambda):
     """
     # Initialize some useful values
     m = y.size  # number of training examples
+    J = 0.0
+    grad = 0.0
 
     # ====================== YOUR CODE HERE ===================================
     # Instructions: Compute the cost and gradient of regularized linear