Adding introspective training scenario tests.

Author: Rogan Carr

test/Microsoft.ML.Functional.Tests/Common.cs

@@ -267,5 +267,20 @@ public static void AssertMetricsStatistics(RegressionMetricsStatistics metrics)
             AssertMetricStatistics(metrics.RSquared);
             AssertMetricStatistics(metrics.LossFn);
         }
+
+        /// <summary>
+        /// Verify that a numerical array has no NaNs or infinities.
+        /// </summary>
+        /// <param name="array">An array of doubles.</param>
+        public static void AssertFiniteNumbers(double[] array, int ignoreElementAt = -1)
+        {
+            for (int i = 0; i < array.Length; i++)
+            {
+                if (i == ignoreElementAt)
+                    continue;
+                Assert.False(double.IsNaN(array[i]));
+                Assert.True(double.IsFinite(array[i]));
+            }
+        }
     }
 }

test/Microsoft.ML.Functional.Tests/Evaluation.cs

@@ -237,17 +237,12 @@ public void TrainAndEvaluateRegression()
         {
             var mlContext = new MLContext(seed: 1, conc: 1);
 
-            // Get the dataset.
-            var data = mlContext.Data.CreateTextLoader(TestDatasets.housing.GetLoaderColumns(),
-                hasHeader: TestDatasets.housing.fileHasHeader, separatorChar: TestDatasets.housing.fileSeparator)
-                .Load(GetDataPath(TestDatasets.housing.trainFilename));
+            // Get the dataset
+            var data = mlContext.Data.LoadFromTextFile<HousingRegression>(GetDataPath(TestDatasets.housing.trainFilename), hasHeader: true);
 
-            // Create a pipeline to train on the sentiment data.
-            var pipeline = mlContext.Transforms.Concatenate("Features", new string[] {
-                    "CrimesPerCapita", "PercentResidental", "PercentNonRetail", "CharlesRiver", "NitricOxides", "RoomsPerDwelling",
-                    "PercentPre40s", "EmploymentDistance", "HighwayDistance", "TaxRate", "TeacherRatio"})
-                .Append(mlContext.Transforms.CopyColumns("Label", "MedianHomeValue"))
-                .Append(mlContext.Regression.Trainers.FastTree(new FastTreeRegressionTrainer.Options { NumThreads = 1 }));
+            // Create a pipeline to train on the housing data.
+            var pipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
+                .Append(mlContext.Regression.Trainers.FastForest(new FastForestRegression.Options { NumThreads = 1 }));
 
             // Train the model.
             var model = pipeline.Fit(data);