diff --git a/Microsoft.ML.AutoML.sln b/Microsoft.ML.AutoML.sln
new file mode 100644
index 0000000000..0fa15ef556
--- /dev/null
+++ b/Microsoft.ML.AutoML.sln
@@ -0,0 +1,78 @@
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio 15
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+MinimumVisualStudioVersion = 10.0.40219.1
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+EndProject
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+EndProject
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+EndProject
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+EndProject
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+ Debug|Any CPU = Debug|Any CPU
+ Debug-Intrinsics|Any CPU = Debug-Intrinsics|Any CPU
+ Debug-netfx|Any CPU = Debug-netfx|Any CPU
+ Release|Any CPU = Release|Any CPU
+ Release-Intrinsics|Any CPU = Release-Intrinsics|Any CPU
+ Release-netfx|Any CPU = Release-netfx|Any CPU
+ EndGlobalSection
+ GlobalSection(ProjectConfigurationPlatforms) = postSolution
+ {B3727729-3DF8-47E0-8710-9B41DAF55817}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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+ {AAC3E4E6-C146-44BB-8873-A1E61D563F2A}.Release-netfx|Any CPU.Build.0 = Release-netfx|Any CPU
+ EndGlobalSection
+ GlobalSection(SolutionProperties) = preSolution
+ HideSolutionNode = FALSE
+ EndGlobalSection
+ GlobalSection(ExtensibilityGlobals) = postSolution
+ SolutionGuid = {8C1BC26C-B87E-47CD-928E-00EFE4353B40}
+ EndGlobalSection
+EndGlobal
diff --git a/Microsoft.ML.sln b/Microsoft.ML.sln
index daa4ff4511..6b0b880210 100644
--- a/Microsoft.ML.sln
+++ b/Microsoft.ML.sln
@@ -274,14 +274,6 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Microsoft.ML.FastTree", "Mi
pkg\Microsoft.ML.FastTree\Microsoft.ML.FastTree.symbols.nupkgproj = pkg\Microsoft.ML.FastTree\Microsoft.ML.FastTree.symbols.nupkgproj
EndProjectSection
EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Microsoft.ML.Auto", "src\Microsoft.ML.Auto\Microsoft.ML.Auto.csproj", "{D57A04E8-1A2B-4A3E-A96A-229C746C2FBE}"
-EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Microsoft.ML.AutoML.Tests", "test\Microsoft.ML.AutoML.Tests\Microsoft.ML.AutoML.Tests.csproj", "{D48126A1-5334-4575-BC91-4CDAA754C8C8}"
-EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "mlnet", "src\mlnet\mlnet.csproj", "{C2F953F9-9825-48AB-88D8-D4538268F017}"
-EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "mlnet.Tests", "test\mlnet.Tests\mlnet.Tests.csproj", "{73D4685B-94D2-4C28-A434-16ED6CA39BDE}"
-EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|Any CPU = Debug|Any CPU
@@ -976,54 +968,6 @@ Global
{E02DA82D-3FEE-4C60-BD80-9EC3C3448DFC}.Release-Intrinsics|Any CPU.Build.0 = Release-Intrinsics|Any CPU
{E02DA82D-3FEE-4C60-BD80-9EC3C3448DFC}.Release-netfx|Any CPU.ActiveCfg = Release-netfx|Any CPU
{E02DA82D-3FEE-4C60-BD80-9EC3C3448DFC}.Release-netfx|Any CPU.Build.0 = Release-netfx|Any CPU
- {D57A04E8-1A2B-4A3E-A96A-229C746C2FBE}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
@@ -1111,10 +1055,6 @@ Global
{AD7058C9-5608-49A8-BE23-58C33A74EE91} = {D3D38B03-B557-484D-8348-8BADEE4DF592}
{E02DA82D-3FEE-4C60-BD80-9EC3C3448DFC} = {09EADF06-BE25-4228-AB53-95AE3E15B530}
{B1B3F284-FA3D-4D76-A712-FF04495D244B} = {D3D38B03-B557-484D-8348-8BADEE4DF592}
- {D57A04E8-1A2B-4A3E-A96A-229C746C2FBE} = {09EADF06-BE25-4228-AB53-95AE3E15B530}
- {D48126A1-5334-4575-BC91-4CDAA754C8C8} = {AED9C836-31E3-4F3F-8ABC-929555D3F3C4}
- {C2F953F9-9825-48AB-88D8-D4538268F017} = {09EADF06-BE25-4228-AB53-95AE3E15B530}
- {73D4685B-94D2-4C28-A434-16ED6CA39BDE} = {AED9C836-31E3-4F3F-8ABC-929555D3F3C4}
EndGlobalSection
GlobalSection(ExtensibilityGlobals) = postSolution
SolutionGuid = {41165AF1-35BB-4832-A189-73060F82B01D}
diff --git a/build.proj b/build.proj
index 15fea4e309..2099d6cfbf 100644
--- a/build.proj
+++ b/build.proj
@@ -21,6 +21,7 @@
+
diff --git a/docs/samples/Microsoft.ML.Samples/AutoML/BinaryClassificationExperiment.cs b/docs/samples/Microsoft.ML.Samples/AutoML/BinaryClassificationExperiment.cs
deleted file mode 100644
index 2957a2c635..0000000000
--- a/docs/samples/Microsoft.ML.Samples/AutoML/BinaryClassificationExperiment.cs
+++ /dev/null
@@ -1,23 +0,0 @@
-using Microsoft.ML;
-using Microsoft.ML.Auto;
-
-namespace Samples.AutoML
-{
- public static class BinaryClassificationExperiment
- {
- public static void Example()
- {
- // Create a new context for ML.NET operations. It can be used for exception tracking and logging,
- // as a catalog of available operations and as the source of randomness.
- var mlContext = new MLContext();
-
- // Download and featurize the dataset.
- var dataView = Microsoft.ML.SamplesUtils.DatasetUtils.LoadFeaturizedAdultDataset(mlContext);
-
- // Run an AutoML experiment
- var experimentResult = mlContext.Auto()
- .CreateBinaryClassificationExperiment(60)
- .Execute(dataView, "IsOver50K");
- }
- }
-}
diff --git a/docs/samples/Microsoft.ML.Samples/AutoML/BinaryClassificationExperimentWithExperimentSettings.cs b/docs/samples/Microsoft.ML.Samples/AutoML/BinaryClassificationExperimentWithExperimentSettings.cs
deleted file mode 100644
index c383a3963c..0000000000
--- a/docs/samples/Microsoft.ML.Samples/AutoML/BinaryClassificationExperimentWithExperimentSettings.cs
+++ /dev/null
@@ -1,27 +0,0 @@
-using Microsoft.ML;
-using Microsoft.ML.Auto;
-
-namespace Samples.AutoML
-{
- public static class BinaryClassificationExperimentWithExperimentSettings
- {
- public static void Example()
- {
- // Create a new context for ML.NET operations. It can be used for exception tracking and logging,
- // as a catalog of available operations and as the source of randomness.
- var mlContext = new MLContext();
-
- // Download and featurize the dataset.
- var dataView = Microsoft.ML.SamplesUtils.DatasetUtils.LoadFeaturizedAdultDataset(mlContext);
-
- // Run an AutoML experiment
- var experimentSettings = new BinaryExperimentSettings()
- {
- MaxExperimentTimeInSeconds = 60
- };
- var experimentResult = mlContext.Auto()
- .CreateBinaryClassificationExperiment(experimentSettings)
- .Execute(dataView, "IsOver50K");
- }
- }
-}
diff --git a/docs/samples/Microsoft.ML.Samples/AutoML/MulticlassClassificationExperiment.cs b/docs/samples/Microsoft.ML.Samples/AutoML/MulticlassClassificationExperiment.cs
deleted file mode 100644
index bb0b98907c..0000000000
--- a/docs/samples/Microsoft.ML.Samples/AutoML/MulticlassClassificationExperiment.cs
+++ /dev/null
@@ -1,28 +0,0 @@
-using Microsoft.ML;
-using Microsoft.ML.Auto;
-using Microsoft.ML.SamplesUtils;
-
-namespace Samples.AutoML
-{
- public static class MulticlassClassificationExperiment
- {
- public static void Example()
- {
- // Create a new context for ML.NET operations. It can be used for exception tracking and logging,
- // as a catalog of available operations and as the source of randomness.
- var mlContext = new MLContext();
-
- // Download and featurize the dataset.
- // Create a list of data examples.
- var examples = DatasetUtils.GenerateRandomMulticlassClassificationExamples(1000);
-
- // Convert the examples list to an IDataView object, which is consumable by ML.NET API.
- var dataView = mlContext.Data.LoadFromEnumerable(examples);
-
- // Run an AutoML experiment
- var experimentResult = mlContext.Auto()
- .CreateMulticlassClassificationExperiment(60)
- .Execute(dataView);
- }
- }
-}
\ No newline at end of file
diff --git a/docs/samples/Microsoft.ML.Samples/AutoML/MulticlassClassificationExperimentWithExperimentSettings.cs b/docs/samples/Microsoft.ML.Samples/AutoML/MulticlassClassificationExperimentWithExperimentSettings.cs
deleted file mode 100644
index 8056b81d43..0000000000
--- a/docs/samples/Microsoft.ML.Samples/AutoML/MulticlassClassificationExperimentWithExperimentSettings.cs
+++ /dev/null
@@ -1,32 +0,0 @@
-using Microsoft.ML;
-using Microsoft.ML.Auto;
-using Microsoft.ML.SamplesUtils;
-
-namespace Samples.AutoML
-{
- public static class MulticlassClassificationExperimentWithExperimentSettings
- {
- public static void Example()
- {
- // Create a new context for ML.NET operations. It can be used for exception tracking and logging,
- // as a catalog of available operations and as the source of randomness.
- var mlContext = new MLContext();
-
- // Download and featurize the dataset.
- // Create a list of data examples.
- var examples = DatasetUtils.GenerateRandomMulticlassClassificationExamples(1000);
-
- // Convert the examples list to an IDataView object, which is consumable by ML.NET API.
- var dataView = mlContext.Data.LoadFromEnumerable(examples);
-
- // Run an AutoML experiment
- var experimentSettings = new MulticlassExperimentSettings()
- {
- MaxExperimentTimeInSeconds = 60
- };
- var experimentResult = mlContext.Auto()
- .CreateMulticlassClassificationExperiment(experimentSettings)
- .Execute(dataView);
- }
- }
-}
\ No newline at end of file
diff --git a/docs/samples/Microsoft.ML.Samples/AutoML/RegressionExperiment.cs b/docs/samples/Microsoft.ML.Samples/AutoML/RegressionExperiment.cs
deleted file mode 100644
index 79938d02c7..0000000000
--- a/docs/samples/Microsoft.ML.Samples/AutoML/RegressionExperiment.cs
+++ /dev/null
@@ -1,39 +0,0 @@
-using Microsoft.ML;
-using Microsoft.ML.Auto;
-using Microsoft.ML.Data;
-
-namespace Samples.AutoML
-{
- public static class RegressionExperiment
- {
- public static void Example()
- {
- // Downloading a regression dataset from github.com/dotnet/machinelearning
- string dataFile = Microsoft.ML.SamplesUtils.DatasetUtils.DownloadHousingRegressionDataset();
-
- // Create a new context for ML.NET operations. It can be used for exception tracking and logging,
- // as a catalog of available operations and as the source of randomness.
- var mlContext = new MLContext();
-
- // Creating a data loader, based on the format of the data
- // The data is tab separated with all numeric columns.
- // The first column being the label and rest are numeric features
- // Here only seven numeric columns are used as features
- var dataView = mlContext.Data.LoadFromTextFile(dataFile, new TextLoader.Options
- {
- Separators = new[] { '\t' },
- HasHeader = true,
- Columns = new[]
- {
- new TextLoader.Column("Label", DataKind.Single, 0),
- new TextLoader.Column("Features", DataKind.Single, 1, 6)
- }
- });
-
- // Run an AutoML experiment
- var experimentResult = mlContext.Auto()
- .CreateRegressionExperiment(60)
- .Execute(dataView);
- }
- }
-}
diff --git a/docs/samples/Microsoft.ML.Samples/AutoML/RegressionExperimentWithExperimentSettings.cs b/docs/samples/Microsoft.ML.Samples/AutoML/RegressionExperimentWithExperimentSettings.cs
deleted file mode 100644
index 9d9dd061e4..0000000000
--- a/docs/samples/Microsoft.ML.Samples/AutoML/RegressionExperimentWithExperimentSettings.cs
+++ /dev/null
@@ -1,43 +0,0 @@
-using Microsoft.ML;
-using Microsoft.ML.Auto;
-using Microsoft.ML.Data;
-
-namespace Samples.AutoML
-{
- public static class RegressionExperimentWithExperimentSettings
- {
- public static void Example()
- {
- // Downloading a regression dataset from github.com/dotnet/machinelearning
- string dataFile = Microsoft.ML.SamplesUtils.DatasetUtils.DownloadHousingRegressionDataset();
-
- // Create a new context for ML.NET operations. It can be used for exception tracking and logging,
- // as a catalog of available operations and as the source of randomness.
- var mlContext = new MLContext();
-
- // Creating a data loader, based on the format of the data
- // The data is tab separated with all numeric columns.
- // The first column being the label and rest are numeric features
- // Here only seven numeric columns are used as features
- var dataView = mlContext.Data.LoadFromTextFile(dataFile, new TextLoader.Options
- {
- Separators = new[] { '\t' },
- HasHeader = true,
- Columns = new[]
- {
- new TextLoader.Column("Label", DataKind.Single, 0),
- new TextLoader.Column("Features", DataKind.Single, 1, 6)
- }
- });
-
- // Run an AutoML experiment
- var experimentSettings = new RegressionExperimentSettings()
- {
- MaxExperimentTimeInSeconds = 60
- };
- var experimentResult = mlContext.Auto()
- .CreateRegressionExperiment(60)
- .Execute(dataView);
- }
- }
-}
diff --git a/docs/samples/Microsoft.ML.Samples/Microsoft.ML.Samples.csproj b/docs/samples/Microsoft.ML.Samples/Microsoft.ML.Samples.csproj
index d63f4d0b9c..ea16ed7bf3 100644
--- a/docs/samples/Microsoft.ML.Samples/Microsoft.ML.Samples.csproj
+++ b/docs/samples/Microsoft.ML.Samples/Microsoft.ML.Samples.csproj
@@ -9,7 +9,6 @@
-
diff --git a/src/Microsoft.ML.Auto/API/AutoCatalog.cs b/src/Microsoft.ML.Auto/API/AutoCatalog.cs
index bd07b1fcb3..98e28e4885 100644
--- a/src/Microsoft.ML.Auto/API/AutoCatalog.cs
+++ b/src/Microsoft.ML.Auto/API/AutoCatalog.cs
@@ -31,13 +31,6 @@ internal AutoCatalog(MLContext context)
/// but was the number of seconds in 6 hours,
/// the experiment will run for 4 + 5 = 9 hours (not 6 hours).
///
- ///
- ///
- ///
- ///
- ///
public RegressionExperiment CreateRegressionExperiment(uint maxExperimentTimeInSeconds)
{
return new RegressionExperiment(_context, new RegressionExperimentSettings()
@@ -51,13 +44,6 @@ public RegressionExperiment CreateRegressionExperiment(uint maxExperimentTimeInS
///
/// Settings for the AutoML experiment.
/// A new AutoML regression experiment.
- ///
- ///
- ///
- ///
- ///
public RegressionExperiment CreateRegressionExperiment(RegressionExperimentSettings experimentSettings)
{
return new RegressionExperiment(_context, experimentSettings);
@@ -76,13 +62,6 @@ public RegressionExperiment CreateRegressionExperiment(RegressionExperimentSetti
/// but was the number of seconds in 6 hours,
/// the experiment will run for 4 + 5 = 9 hours (not 6 hours).
///
- ///
- ///
- ///
- ///
- ///
public BinaryClassificationExperiment CreateBinaryClassificationExperiment(uint maxExperimentTimeInSeconds)
{
return new BinaryClassificationExperiment(_context, new BinaryExperimentSettings()
@@ -96,13 +75,6 @@ public BinaryClassificationExperiment CreateBinaryClassificationExperiment(uint
///
/// Settings for the AutoML experiment.
/// A new AutoML binary classification experiment.
- ///
- ///
- ///
- ///
- ///
public BinaryClassificationExperiment CreateBinaryClassificationExperiment(BinaryExperimentSettings experimentSettings)
{
return new BinaryClassificationExperiment(_context, experimentSettings);
@@ -121,13 +93,6 @@ public BinaryClassificationExperiment CreateBinaryClassificationExperiment(Binar
/// but was the number of seconds in 6 hours,
/// the experiment will run for 4 + 5 = 9 hours (not 6 hours).
///
- ///
- ///
- ///
- ///
- ///
public MulticlassClassificationExperiment CreateMulticlassClassificationExperiment(uint maxExperimentTimeInSeconds)
{
return new MulticlassClassificationExperiment(_context, new MulticlassExperimentSettings()
@@ -141,13 +106,6 @@ public MulticlassClassificationExperiment CreateMulticlassClassificationExperime
///
/// Settings for the AutoML experiment.
/// A new AutoML multiclass classification experiment.
- ///
- ///
- ///
- ///
- ///
public MulticlassClassificationExperiment CreateMulticlassClassificationExperiment(MulticlassExperimentSettings experimentSettings)
{
return new MulticlassClassificationExperiment(_context, experimentSettings);
diff --git a/src/Microsoft.ML.Auto/AutoMlUtils.cs b/src/Microsoft.ML.Auto/AutoMlUtils.cs
index 1ee5570ee3..93320b3bf6 100644
--- a/src/Microsoft.ML.Auto/AutoMlUtils.cs
+++ b/src/Microsoft.ML.Auto/AutoMlUtils.cs
@@ -4,7 +4,6 @@
using System;
using System.Threading;
-using Microsoft.ML.Data;
namespace Microsoft.ML.Auto
{
diff --git a/src/Microsoft.ML.Auto/Microsoft.ML.Auto.csproj b/src/Microsoft.ML.Auto/Microsoft.ML.Auto.csproj
index d07b6b91d0..3dc6ce6593 100644
--- a/src/Microsoft.ML.Auto/Microsoft.ML.Auto.csproj
+++ b/src/Microsoft.ML.Auto/Microsoft.ML.Auto.csproj
@@ -10,6 +10,9 @@
+
+
+
@@ -35,17 +38,5 @@
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/src/Microsoft.ML.Auto/TrainerExtensions/SweepableParams.cs b/src/Microsoft.ML.Auto/TrainerExtensions/SweepableParams.cs
index c395103769..9d80ebe09a 100644
--- a/src/Microsoft.ML.Auto/TrainerExtensions/SweepableParams.cs
+++ b/src/Microsoft.ML.Auto/TrainerExtensions/SweepableParams.cs
@@ -53,7 +53,7 @@ private static IEnumerable BuildLbfgsArgsParams()
return new SweepableParam[] {
new SweepableFloatParam("L2Regularization", 0.0f, 1.0f, numSteps: 4),
new SweepableFloatParam("L1Regularization", 0.0f, 1.0f, numSteps: 4),
- new SweepableDiscreteParam("OptimizationTolerance", new object[] { 1e-4f, 1e-7f }),
+ new SweepableDiscreteParam("OptmizationTolerance", new object[] { 1e-4f, 1e-7f }),
new SweepableDiscreteParam("HistorySize", new object[] { 5, 20, 50 }),
new SweepableLongParam("MaximumNumberOfIterations", 1, int.MaxValue),
new SweepableFloatParam("InitialWeightsDiameter", 0.0f, 1.0f, numSteps: 5),
diff --git a/src/mlnet/CodeGenerator/CSharp/TrainerGenerators.cs b/src/mlnet/CodeGenerator/CSharp/TrainerGenerators.cs
index 5a65c31304..ee606a6cde 100644
--- a/src/mlnet/CodeGenerator/CSharp/TrainerGenerators.cs
+++ b/src/mlnet/CodeGenerator/CSharp/TrainerGenerators.cs
@@ -245,7 +245,7 @@ internal override IDictionary NamedParameters
{"FeatureColumnName","featureColumnName" },
{"L1Regularization","l1Regularization" },
{"L2Regularization","l2Regularization" },
- {"OptimizationTolerance","optimizationTolerance" },
+ {"OptmizationTolerance","optimizationTolerance" },
{"HistorySize","historySize" },
{"EnforceNonNegativity","enforceNonNegativity" },
};
@@ -368,7 +368,7 @@ internal override IDictionary NamedParameters
{"FeatureColumnName","featureColumnName" },
{"L1Regularization","l1Regularization" },
{"L2Regularization","l2Regularization" },
- {"OptimizationTolerance","optimizationTolerance" },
+ {"OptmizationTolerance","optimizationTolerance" },
{"HistorySize","historySize" },
{"EnforceNonNegativity","enforceNonNegativity" },
};
diff --git a/src/mlnet/mlnet.csproj b/src/mlnet/mlnet.csproj
index 02be3cc03b..7a2cf20063 100644
--- a/src/mlnet/mlnet.csproj
+++ b/src/mlnet/mlnet.csproj
@@ -116,11 +116,5 @@
ModelBuilder.cs
-
-
-
-
-
-
diff --git a/test/Microsoft.ML.AutoML.Tests/Microsoft.ML.AutoML.Tests.csproj b/test/Microsoft.ML.AutoML.Tests/Microsoft.ML.AutoML.Tests.csproj
index dc4c3b29aa..3a9140e449 100644
--- a/test/Microsoft.ML.AutoML.Tests/Microsoft.ML.AutoML.Tests.csproj
+++ b/test/Microsoft.ML.AutoML.Tests/Microsoft.ML.AutoML.Tests.csproj
@@ -37,11 +37,5 @@
PreserveNewest
-
-
-
-
-
-
diff --git a/test/mlnet.Tests/mlnet.Tests.csproj b/test/mlnet.Tests/mlnet.Tests.csproj
index 85e7da8dd1..c906d577f8 100644
--- a/test/mlnet.Tests/mlnet.Tests.csproj
+++ b/test/mlnet.Tests/mlnet.Tests.csproj
@@ -15,7 +15,6 @@
-