diff --git a/ProgrammingAssignment_1/ProgrammingAssignment1.ipynb b/ProgrammingAssignment_1/ProgrammingAssignment1.ipynb
index 1571a606ddb3d1c44cce5f49d845e09ac63bd17b..3c16e40cd8d6032dad0eef055d240a84b5417213 100644
--- a/ProgrammingAssignment_1/ProgrammingAssignment1.ipynb
+++ b/ProgrammingAssignment_1/ProgrammingAssignment1.ipynb
@@ -163,7 +163,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can start implementing our *k*-NN classifier. *k*-NN class inherits Model class. Use the \"distance\" function you defined above. \"fit\" method takes *k* as an argument. \"predict\" takes as input an *mxd* array containing *d*-dimensional *m* feature vectors for examples and outputs the predicted class and the ratio of positive examples in *k* nearest neighbors."
+    "We can start implementing our *k*-NN classifier. *k*-NN class inherits Model class. Use the \"distance\" function you defined above. \"fit\" method takes *k* as an argument. \"predict\" takes as input an *mxd* array containing *d*-dimensional *m* feature vectors for examples and for each input point outputs the predicted class and the ratio of positive examples in *k* nearest neighbors."
    ]
   },
   {
@@ -213,7 +213,8 @@
     "            test_features: ndarray\n",
     "                mxd array containing features for the points to be predicted\n",
     "        Returns: \n",
-    "            ndarray\n",
+    "            preds: ndarray\n",
+    "                mx2 array containing predicted class and proportion for each test point\n",
     "        '''\n",
     "        raise NotImplementedError\n",
     "        \n",