switch housing dataset to wine

.gitignore

@@ -328,3 +328,5 @@ ASALocalRun/
 
 # MSBuild Binary and Structured Log
 *.binlog
+# Ignore external test datasets.
+/test/data/external/

build.proj

@@ -8,7 +8,7 @@
   <Import Project="$([MSBuild]::GetDirectoryNameOfFileAbove($(MSBuildThisFileDirectory), Directory.Build.props))\Directory.Build.props" />
 
   <Import Project="$(ToolsDir)VersionTools.targets" Condition="Exists('$(ToolsDir)VersionTools.targets')" />
-
+  <UsingTask TaskName="DownloadFilesFromUrl" AssemblyFile="$(ToolsDir)Microsoft.DotNet.Build.Tasks.dll"/>
   <PropertyGroup>
     <!-- To disable the restoration of packages, set RestoreDuringBuild=false or pass /p:RestoreDuringBuild=false.-->
     <RestoreDuringBuild Condition="'$(RestoreDuringBuild)'==''">true</RestoreDuringBuild>
@@ -33,6 +33,7 @@
       RestoreProjects;
       BuildNative;
       $(TraversalBuildDependsOn);
+      DownloadExternalTestFiles;
       RunTests;
     </TraversalBuildDependsOn>
   </PropertyGroup>
@@ -56,13 +57,26 @@
     <ItemGroup>
       <PkgProject Include="pkg\**\*.nupkgproj" />
     </ItemGroup>
-    
+
     <MSBuild Projects="@(PkgProject)"
              Targets="Restore" />
     <MSBuild Projects="@(PkgProject)"
              Targets="Pack" />
   </Target>
 
+  <ItemGroup>
+    <TestFile Include="$(MSBuildThisFileDirectory)/test/data/external/winequality-white.csv"
+      Url="https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv"
+      DestinationFile="$(MSBuildThisFileDirectory)test/data/external/winequality-white.csv" />
+  </ItemGroup>
+
+  <Target Name="DownloadExternalTestFiles" Inputs="@(TestFile)" Outputs="%(TestFile.DestinationFile)">
+    <Message Importance="High" Text="Downloading external test files... %(TestFile.DestinationFile)" />
+    <DownloadFilesFromUrl Items="@(TestFile)"
+                         DestinationDir="test/data/external"
+                         TreatErrorsAsWarnings="true"/>
+  </Target>
+
   <Target Name="RunTests" Condition="'$(RunTests)'=='true'">
     <MSBuild Projects="test\run-tests.proj"
              Targets="RunTests" />

test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs

@@ -4,6 +4,7 @@
 
 using ML = Microsoft.ML;
 using Microsoft.ML.Runtime;
+using Microsoft.ML.Data;
 using Microsoft.ML.Runtime.Data;
 using Microsoft.ML.Runtime.EntryPoints;
 using Microsoft.ML.TestFramework;
@@ -269,10 +270,10 @@ public void TestCrossValidationBinaryMacro()
             }
         }
 
-        [Fact(Skip = "Missing data set. See https://github.com/dotnet/machinelearning/issues/3")]
+        [Fact]
         public void TestCrossValidationMacro()
         {
-            var dataPath = GetDataPath(@"housing.txt");
+            var dataPath = GetDataPath(TestDatasets.winequality.trainFilename);
             using (var env = new TlcEnvironment())
             {
                 var subGraph = env.CreateExperiment();
@@ -295,7 +296,30 @@ public void TestCrossValidationMacro()
                 var modelCombineOutput = subGraph.Add(modelCombine);
 
                 var experiment = env.CreateExperiment();
-                var importInput = new ML.Data.TextLoader(dataPath);
+                var importInput = new ML.Data.TextLoader(dataPath)
+                {
+                    Arguments = new TextLoaderArguments
+                    {
+                        Separator = new[] { ';' },
+                        HasHeader = true,
+                        Column = new[]
+                    {
+                        new TextLoaderColumn()
+                        {
+                            Name = "Label",
+                            Source = new [] { new TextLoaderRange(11) },
+                            Type = DataKind.Num
+                        },
+
+                        new TextLoaderColumn()
+                        {
+                            Name = "Features",
+                            Source = new [] { new TextLoaderRange(0,10) },
+                            Type = DataKind.Num
+                        }
+                    }
+                    }
+                };
                 var importOutput = experiment.Add(importInput);
 
                 var crossValidate = new ML.Models.CrossValidator
@@ -324,7 +348,7 @@ public void TestCrossValidationMacro()
                     Assert.True(b);
                     double val = 0;
                     getter(ref val);
-                    Assert.Equal(3.32, val, 1);
+                    Assert.Equal(0.58, val, 1);
                     b = cursor.MoveNext();
                     Assert.False(b);
                 }

test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs

@@ -910,7 +910,7 @@ public void EntryPointTextToKeyToText()
         }
 
         private void RunTrainScoreEvaluate(string learner, string evaluator, string dataPath, string warningsPath, string overallMetricsPath,
-                    string instanceMetricsPath, string confusionMatrixPath = null)
+                    string instanceMetricsPath, string confusionMatrixPath = null, string loader = null)
         {
             string inputGraph = string.Format(@"
                 {{
@@ -919,6 +919,7 @@ private void RunTrainScoreEvaluate(string learner, string evaluator, string data
                       'Name': 'Data.CustomTextLoader',
                       'Inputs': {{
                         'InputFile': '$file'
+                        {8}
                       }},
                       'Outputs': {{
                         'Data': '$AllData'
@@ -978,7 +979,8 @@ private void RunTrainScoreEvaluate(string learner, string evaluator, string data
                   }}
                 }}", learner, evaluator, EscapePath(dataPath), EscapePath(warningsPath), EscapePath(overallMetricsPath), EscapePath(instanceMetricsPath),
                 confusionMatrixPath != null ? ", 'ConfusionMatrix': '$ConfusionMatrix'" : "",
-                confusionMatrixPath != null ? string.Format(", 'ConfusionMatrix' : '{0}'", EscapePath(confusionMatrixPath)) : "");
+                confusionMatrixPath != null ? string.Format(", 'ConfusionMatrix' : '{0}'", EscapePath(confusionMatrixPath)) : "",
+                string.IsNullOrWhiteSpace(loader) ? "" : string.Format(",'CustomSchema': '{0}'", loader));
 
             var jsonPath = DeleteOutputPath("graph.json");
             File.WriteAllLines(jsonPath, new[] { inputGraph });
@@ -1036,15 +1038,16 @@ public void EntryPointEvaluateMultiClass()
                 Assert.Equal(3, CountRows(loader));
         }
 
-        [Fact(Skip = "Missing data set. See https://github.com/dotnet/machinelearning/issues/3")]
+        [Fact]
         public void EntryPointEvaluateRegression()
         {
-            var dataPath = GetDataPath("housing.txt");
+            var dataPath = GetDataPath(TestDatasets.winequality.trainFilename);
             var warningsPath = DeleteOutputPath("warnings.idv");
             var overallMetricsPath = DeleteOutputPath("overall.idv");
             var instanceMetricsPath = DeleteOutputPath("instance.idv");
 
-            RunTrainScoreEvaluate("Trainers.StochasticDualCoordinateAscentRegressor", "Models.RegressionEvaluator", dataPath, warningsPath, overallMetricsPath, instanceMetricsPath);
+            RunTrainScoreEvaluate("Trainers.StochasticDualCoordinateAscentRegressor", "Models.RegressionEvaluator",
+                dataPath, warningsPath, overallMetricsPath, instanceMetricsPath, loader: TestDatasets.winequality.loaderSettings);
 
             using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath))
                 Assert.Equal(0, CountRows(loader));
@@ -1053,7 +1056,7 @@ public void EntryPointEvaluateRegression()
                 Assert.Equal(1, CountRows(loader));
 
             using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath))
-                Assert.Equal(104, CountRows(loader));
+                Assert.Equal(975, CountRows(loader));
         }
 
         [Fact]
@@ -1068,10 +1071,10 @@ public void EntryPointSDCAMultiClass()
             TestEntryPointRoutine("iris.txt", "Trainers.StochasticDualCoordinateAscentClassifier");
         }
 
-        [Fact(Skip = "Missing data set. See https://github.com/dotnet/machinelearning/issues/3")]
+        [Fact()]
         public void EntryPointSDCARegression()
         {
-            TestEntryPointRoutine("housing.txt", "Trainers.StochasticDualCoordinateAscentRegressor");
+            TestEntryPointRoutine(TestDatasets.winequality.trainFilename, "Trainers.StochasticDualCoordinateAscentRegressor", loader: TestDatasets.winequality.loaderSettings);
         }
 
         [Fact]
@@ -1142,10 +1145,10 @@ public void EntryPointHogwildSGD()
             TestEntryPointRoutine("breast-cancer.txt", "Trainers.StochasticGradientDescentBinaryClassifier");
         }
 
-        [Fact(Skip = "Missing data set. See https://github.com/dotnet/machinelearning/issues/3")]
+        [Fact()]
         public void EntryPointPoissonRegression()
         {
-            TestEntryPointRoutine("housing.txt", "Trainers.PoissonRegressor");
+            TestEntryPointRoutine(TestDatasets.winequality.trainFilename, "Trainers.PoissonRegressor", loader: TestDatasets.winequality.loaderSettings);
         }
 
         [Fact]

test/Microsoft.ML.TestFramework/Datasets.cs

@@ -152,6 +152,14 @@ public static class TestDatasets
             testFilename = "housing.txt"
         };
 
+        public static TestDataset winequality = new TestDataset
+        {
+            name = "wine",
+            trainFilename = "external/winequality-white.csv",
+            testFilename = "external/winequality-white.csv",
+            loaderSettings = "col=Label:R4:11 col=Features:R4:0-10 sep=; header+"
+        };
+
         public static TestDataset msm = new TestDataset
         {
             // REVIEW: Why is the MSM train set smaller than the test set? Reverse these!

test/Microsoft.ML.Tests/Microsoft.ML.Tests.csproj

@@ -8,6 +8,6 @@
 
   <ItemGroup>
     <NativeAssemblyReference Include="CpuMathNative" />
-	<NativeAssemblyReference Include="FastTreeNative" />
+    <NativeAssemblyReference Include="FastTreeNative" />
   </ItemGroup>
 </Project>