donors update

projects/finding_donors/finding_donors.ipynb

@@ -344,6 +344,8 @@
     "### Question 1 - Naive Predictor Performace\n",
     "* If we chose a model that always predicted an individual made more than $50,000, what would  that model's accuracy and F-score be on this dataset? You must use the code cell below and assign your results to `'accuracy'` and `'fscore'` to be used later.\n",
     "\n",
+    "** Please note ** that the the purpose of generating a naive predictor is simply to show what a base model without any intelligence would look like. In the real world, ideally your base model would be either the results of a previous model or could be based on a research paper upon which you are looking to improve. When there is no benchmark model set, getting a result better than random choice is a place you could start from.\n",
+    "\n",
     "** HINT: ** \n",
     "\n",
     "* When we have a model that always predicts '1' (i.e. the individual makes more than 50k) then our model will have no True Negatives(TN) or False Negatives(FN) as we are not making any negative('0' value) predictions. Therefore our Accuracy in this case becomes the same as our Precision(True Positives/(True Positives + False Positives)) as every prediction that we have made with value '1' that should have '0' becomes a False Positive; therefore our denominator in this case is the total number of records we have in total. \n",
@@ -677,10 +679,10 @@
    "source": [
     "#### Results:\n",
     "\n",
-    "|     Metric     | Benchmark Predictor | Unoptimized Model | Optimized Model |\n",
-    "| :------------: | :-----------------: | :---------------: | :-------------: | \n",
-    "| Accuracy Score |                     |                   |                 |\n",
-    "| F-score        |                     |                   |   EXAMPLE       |\n"
+    "|     Metric     | Unoptimized Model | Optimized Model |\n",
+    "| :------------: | :---------------: | :-------------: | \n",
+    "| Accuracy Score |                   |                 |\n",
+    "| F-score        |                   |   EXAMPLE       |\n"
    ]
   },
   {