Remove legacy API test that already have coverage and refactor code.

test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs

@@ -45,5 +45,41 @@ public void New_SimpleTrainAndPredict()
                 Assert.True(input.Sentiment && prediction.Score > 1 || !input.Sentiment && prediction.Score < -1);
             }
         }
+
+        /// <summary>
+        /// Start with a dataset in a text file. Run text featurization on text values. 
+        /// Train a linear model over that. (I am thinking sentiment classification.) 
+        /// Out of the result, produce some structure over which you can get predictions programmatically 
+        /// (for example, the prediction does not happen over a file as it did during training).
+        /// Uses Symbolic SDCA Trainer.
+        /// </summary>
+        [Fact]
+        public void SimpleTrainAndPredictSymSGD()
+        {
+            var ml = new MLContext(seed: 1, conc: 1);
+            var data = ml.Data.ReadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.trainFilename), hasHeader: true);
+
+            // Pipeline.
+            var pipeline = ml.Transforms.Text.FeaturizeText("SentimentText", "Features")
+                .AppendCacheCheckpoint(ml)
+                .Append(ml.BinaryClassification.Trainers.SymbolicStochasticGradientDescent("Label", "Features", advancedSettings: s => s.NumberOfThreads = 1));
+
+            // Train.
+            var model = pipeline.Fit(data);
+
+            // Create prediction engine and test predictions.
+            var engine = model.CreatePredictionEngine<SentimentData, SentimentPrediction>(ml);
+
+            // Take a couple examples out of the test data and run predictions on top.
+            var testData = ml.Data.ReadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.testFilename), hasHeader: true)
+                .AsEnumerable<SentimentData>(ml, false);
+            foreach (var input in testData.Take(5))
+            {
+                var prediction = engine.Predict(input);
+                // Verify that predictions match and scores are separated from zero.
+                Assert.Equal(input.Sentiment, prediction.Sentiment);
+                Assert.True(input.Sentiment && prediction.Score > 1 || !input.Sentiment && prediction.Score < -1);
+            }
+        }
     }
 }