Refactored scenario tests (issue #32)

test/Microsoft.ML.Tests/Scenarios/Scenario_HousePricePrediction.cs → test/Microsoft.ML.Tests/Scenarios/HousePricePredictionTests.cs

@@ -2,14 +2,17 @@
 // The .NET Foundation licenses this file to you under the MIT license.
 // See the LICENSE file in the project root for more information.
 
+using Microsoft.ML.Models;
 using Microsoft.ML.Runtime.Api;
 using Microsoft.ML.TestFramework;
+using Microsoft.ML.Trainers;
+using Microsoft.ML.Transforms;
 using Xunit;
 using Xunit.Abstractions;
 
 namespace Microsoft.ML.Scenarios
 {
-    public partial class Top5Scenarios : BaseTestClass
+    public partial class ScenariosTests : BaseTestClass
     {
         /*
          A real-estate firm Contoso wants to add a house price prediction to their ASP.NET/Xamarin application.
@@ -49,6 +52,64 @@ public async void PredictHousePriceModelTest()
             Assert.InRange(prediction.Price, 260_000, 330_000);
         }
 
+        [Fact(Skip = "Missing data set. See https://github.com/dotnet/machinelearning/issues/3")]
+        public void TrainAndPredictHousePriceModelTest()
+        {
+            string dataPath = GetDataPath("kc_house_data.csv");
+
+            var pipeline = new LearningPipeline();
+
+            pipeline.Add(new TextLoader<HousePriceData>(dataPath, useHeader: true, separator: ","));
+
+            pipeline.Add(new ColumnConcatenator(outputColumn: "NumericalFeatures",
+                "SqftLiving", "SqftLot", "SqftAbove", "SqftBasement", "Lat", "Long", "SqftLiving15", "SqftLot15"));
+
+            pipeline.Add(new ColumnConcatenator(outputColumn: "CategoryFeatures",
+                 "Bedrooms", "Bathrooms", "Floors", "Waterfront", "View", "Condition", "Grade", "YearBuilt", "YearRenovated", "Zipcode"));
+
+            pipeline.Add(new CategoricalOneHotVectorizer("CategoryFeatures"));
+            pipeline.Add(new ColumnConcatenator(outputColumn: "Features",
+                "NumericalFeatures", "CategoryFeatures"));
+            pipeline.Add(new StochasticDualCoordinateAscentRegressor());
+
+            PredictionModel<HousePriceData, HousePricePrediction> model = pipeline.Train<HousePriceData, HousePricePrediction>();
+
+            HousePricePrediction prediction = model.Predict(new HousePriceData()
+            {
+                Bedrooms = 3,
+                Bathrooms = 2,
+                SqftLiving = 1710,
+                SqftLot = 4697,
+                Floors = 1.5f,
+                Waterfront = 0,
+                View = 0,
+                Condition = 5,
+                Grade = 6,
+                SqftAbove = 1710,
+                SqftBasement = 0,
+                YearBuilt = 1941,
+                YearRenovated = 0,
+                Zipcode = 98002,
+                Lat = 47.3048f,
+                Long = -122.218f,
+                SqftLiving15 = 1030,
+                SqftLot15 = 4705
+            });
+
+            Assert.InRange(prediction.Price, 260_000, 330_000);
+
+            string testDataPath = GetDataPath("kc_house_test.csv");
+            var testData = new TextLoader<HousePriceData>(testDataPath, useHeader: true, separator: ",");
+
+            var evaluator = new RegressionEvaluator();
+            RegressionMetrics metrics = evaluator.Evaluate(model, testData);
+            Assert.InRange(metrics.L1, 85_000, 89_000);
+            Assert.InRange(metrics.L2, 17_000_000_000, 19_000_000_000);
+            Assert.InRange(metrics.Rms, 130_500, 135_000);
+            Assert.InRange(metrics.LossFn, 17_000_000_000, 19_000_000_000);
+            Assert.Equal(.8, metrics.RSquared, 1);
+        }
+
         public class HousePriceData
         {
             [Column(ordinal: "0")]
@@ -121,7 +182,7 @@ public class HousePricePrediction
             public float Price;
         }
 
-        public Top5Scenarios(ITestOutputHelper output) : base(output)
+        public ScenariosTests(ITestOutputHelper output) : base(output)
         {
         }
     }

test/Microsoft.ML.Tests/Scenarios/TrainAndPredictIrisModelTest.cs → test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs

@@ -10,7 +10,7 @@
 
 namespace Microsoft.ML.Scenarios
 {
-    public partial class Top5Scenarios
+    public partial class ScenariosTests
     {
         [Fact]
         public void TrainAndPredictIrisModelTest()

test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs → test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs

@@ -13,7 +13,7 @@
 
 namespace Microsoft.ML.Scenarios
 {
-    public partial class Top5Scenarios
+    public partial class ScenariosTests
     {
         public const string SentimentDataPath = "wikipedia-detox-250-line-data.tsv";
         public const string SentimentTestPath = "wikipedia-detox-250-line-test.tsv";