diff --git a/server/analysis/nn_tf.py b/server/analysis/nn_tf.py
index 1c370d7..d24b524 100644
--- a/server/analysis/nn_tf.py
+++ b/server/analysis/nn_tf.py
@@ -34,7 +34,8 @@ class NeuralNet(object):
                  batch_size=1,
                  explore_iters=500,
                  noise_scale_begin=0.1,
-                 noise_scale_end=0):
+                 noise_scale_end=0,
+                 reset_seed=False):
 
         self.history = None
         self.recommend_iters = 0
@@ -49,6 +50,9 @@ class NeuralNet(object):
         self.vars = {}
         self.ops = {}
 
+        tf.reset_default_graph()
+        if reset_seed:
+            tf.set_random_seed(0)
         self.session = tf.Session()
         self.graph = tf.get_default_graph()
         with self.graph.as_default():
diff --git a/server/analysis/tests/test_nn.py b/server/analysis/tests/test_nn.py
index 302e2ee..0f9803d 100644
--- a/server/analysis/tests/test_nn.py
+++ b/server/analysis/tests/test_nn.py
@@ -26,17 +26,18 @@ class TestNN(unittest.TestCase):
         np.random.seed(0)
         set_random_seed(0)
         cls.model = NeuralNet(n_input=X_test.shape[1],
-                              batch_size=X_test.shape[0])
+                              batch_size=X_test.shape[0],
+                              reset_seed=True)
         cls.model.fit(X_train, y_train)
         cls.nn_result = cls.model.predict(X_test)
         cls.nn_recommend = cls.model.recommend(X_test)
 
     def test_nn_ypreds(self):
         ypreds_round = ['%.3f' % x[0] for x in self.nn_result]
-        expected_ypreds = ['20.021', '22.578', '22.722', '26.889', '24.362', '23.258']
+        expected_ypreds = ['21.279', '22.668', '23.115', '27.228', '25.892', '23.967']
         self.assertEqual(ypreds_round, expected_ypreds)
 
     def test_nn_yrecommend(self):
         recommends_round = ['%.3f' % x[0] for x in self.nn_recommend.minl]
-        expected_recommends = ['13.321', '15.482', '15.621', '18.648', '16.982', '15.986']
+        expected_recommends = ['21.279', '21.279', '21.279', '21.279', '21.279', '21.279']
         self.assertEqual(recommends_round, expected_recommends)