resolving review comments

Author: artidoro

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/PriorTrainerSample.cs

@@ -58,6 +58,8 @@ public static void Example()
             // Step 5: Inspect the output
             Console.WriteLine("Accuracy: " + evalMetrics.Accuracy);
 
+            // The Prior trainer outputs the proportion of a label in the dataset as the probability of that label.
+            // In this case it means that there is a split of around 64%-36% of positive and negative labels in the dataset.
             // Expected output:
             // Accuracy: 0.647058823529412
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/RandomTrainerSample.cs

@@ -58,6 +58,8 @@ public static void Example()
             // Step 5: Inspect the output
             Console.WriteLine("Accuracy: " + evalMetrics.Accuracy);
 
+            // We expect an output probability closet to 0.5 as the Random trainer outputs a random prediction.
+            // Regardless of the input features, the trainer will predict either positive or negative label with equal probability.
             // Expected output (close to 0.5):
             // Accuracy: 0.588235294117647
         }