BinaryClassificationTrainers
AveragedPerceptron(BinaryClassificationTrainers, Options)
AveragedPerceptron(BinaryClassificationTrainers, String, String, IClassificationLoss, Single, Boolean, Single, Int32)
AveragedPerceptron(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, IClassificationLoss, Options, Action<LinearBinaryModelParameters>)
AveragedPerceptron(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, IClassificationLoss, Single, Boolean, Single, Int32, Action<LinearBinaryModelParameters>)
FastForest(BinaryClassificationTrainers, Options)
FastForest(BinaryClassificationTrainers, String, String, String, Int32, Int32, Int32)
FastTree(BinaryClassificationTrainers, Options)
FastTree(BinaryClassificationTrainers, String, String, String, Int32, Int32, Int32, Double)
FastTree(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Options, Action<CalibratedModelParametersBase<FastTreeBinaryModelParameters, PlattCalibrator>>)
FastTree(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Int32, Int32, Int32, Double, Action<CalibratedModelParametersBase<FastTreeBinaryModelParameters, PlattCalibrator>>)
FieldAwareFactorizationMachine(BinaryClassificationTrainers, Options)
FieldAwareFactorizationMachine(BinaryClassificationTrainers, String, String, String)
FieldAwareFactorizationMachine(BinaryClassificationTrainers, String[], String, String)
FieldAwareFactorizationMachine(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>[], Action<FieldAwareFactorizationMachineModelParameters>)
FieldAwareFactorizationMachine(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>[], Options, Action<FieldAwareFactorizationMachineModelParameters>)
Gam(BinaryClassificationTrainers, Options)
Gam(BinaryClassificationTrainers, String, String, String, Int32, Int32, Double)
LbfgsLogisticRegression(BinaryClassificationTrainers, Options)
LbfgsLogisticRegression(BinaryClassificationTrainers, String, String, String, Single, Single, Single, Int32, Boolean)
LbfgsLogisticRegression(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Options, Action<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>)
LbfgsLogisticRegression(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Single, Single, Single, Int32, Boolean, Action<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>)
LdSvm(BinaryClassificationTrainers, Options)
LdSvm(BinaryClassificationTrainers, String, String, String, Int32, Int32, Boolean, Boolean)
LightGbm(BinaryClassificationTrainers, Options)
LightGbm(BinaryClassificationTrainers, Stream, String)
LightGbm(BinaryClassificationTrainers, String, String, String, Int32?, Int32?, Double?, Int32)
LinearSvm(BinaryClassificationTrainers, Options)
LinearSvm(BinaryClassificationTrainers, String, String, String, Int32)
Prior(BinaryClassificationTrainers, String, String)
Sdca(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Options, Action<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>)
Sdca(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Nullable<Single>, Nullable<Single>, Nullable<Int32>, Action<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>)
SdcaLogisticRegression(BinaryClassificationTrainers, Options)
SdcaLogisticRegression(BinaryClassificationTrainers, String, String, String, Single?, Single?, Int32?)
SdcaNonCalibrated(BinaryClassificationTrainers, Options)
SdcaNonCalibrated(BinaryClassificationTrainers, String, String, String, ISupportSdcaClassificationLoss, Single?, Single?, Int32?)
SdcaNonCalibrated(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, ISupportSdcaClassificationLoss, Options, Action<LinearBinaryModelParameters>)
SdcaNonCalibrated(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, ISupportSdcaClassificationLoss, Scalar<Single>, Nullable<Single>, Nullable<Single>, Nullable<Int32>, Action<LinearBinaryModelParameters>)
SgdCalibrated(BinaryClassificationTrainers, Options)
SgdCalibrated(BinaryClassificationTrainers, String, String, String, Int32, Double, Single)
SgdNonCalibrated(BinaryClassificationTrainers, Options)
SgdNonCalibrated(BinaryClassificationTrainers, String, String, String, IClassificationLoss, Int32, Double, Single)
StochasticGradientDescentClassificationTrainer(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Options, Action<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>)
StochasticGradientDescentClassificationTrainer(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Int32, Double, Single, Action<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>)
StochasticGradientDescentNonCalibratedClassificationTrainer(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Options, Action<LinearBinaryModelParameters>)
StochasticGradientDescentNonCalibratedClassificationTrainer(BinaryClassificationTrainers, Scalar<Boolean>, Vector<Single>, Scalar<Single>, Int32, Double, Single, IClassificationLoss, Action<LinearBinaryModelParameters>)
SymbolicSgdLogisticRegression(BinaryClassificationTrainers, Options)
SymbolicSgdLogisticRegression(BinaryClassificationTrainers, String, String, Int32)
net10.0-windows7.0
namespace Microsoft.ML
{
public static class StandardTrainersCatalog
{
public static SgdNonCalibratedTrainer SgdNonCalibrated(this BinaryClassificationTrainers catalog, Options options);
}
}
nuget.org | 0.0 %
Reference this API |
---|---|
.NET | 5.06.07.08.09.010.0 |
.NET Core | 2.02.12.23.03.1 |
.NET Framework | 4.6.14.6.24.74.7.14.7.24.84.8.1 |
.NET Standard | 2.02.1 |
Information specific to net10.0 | |
Platforms | This API is only available when you target a specific platform: |
Windows | 7.0 |
Information specific to net10.0-windows7.0 | |
Assembly | Microsoft.ML.StandardTrainers , Version=1.0.0.0, PublicKeyToken=cc7b13ffcd2ddd51 |
Referencing | Your project needs a package reference to |
Package | Microsoft.ML (5.0.0-preview.1.25127.4) netstandard2.0 |
Platform Restrictions | This API is supported on all platforms. |
- Built-in API
- Package-provided API