StandardTrainersCatalog
AveragedPerceptron(BinaryClassificationTrainers, Options)- AveragedPerceptron(BinaryClassificationTrainers, String, String, IClassificationLoss, Single, Boolean, Single, Int32)
- LbfgsLogisticRegression(BinaryClassificationTrainers, Options)
- LbfgsLogisticRegression(BinaryClassificationTrainers, String, String, String, Single, Single, Single, Int32, Boolean)
- LbfgsMaximumEntropy(MulticlassClassificationTrainers, Options)
- LbfgsMaximumEntropy(MulticlassClassificationTrainers, String, String, String, Single, Single, Single, Int32, Boolean)
- LbfgsPoissonRegression(RegressionTrainers, Options)
- LbfgsPoissonRegression(RegressionTrainers, String, String, String, Single, Single, Single, Int32, Boolean)
- LdSvm(BinaryClassificationTrainers, Options)
- LdSvm(BinaryClassificationTrainers, String, String, String, Int32, Int32, Boolean, Boolean)
- LinearSvm(BinaryClassificationTrainers, Options)
- LinearSvm(BinaryClassificationTrainers, String, String, String, Int32)
- NaiveBayes(MulticlassClassificationTrainers, String, String)
- OneVersusAll<TModel>(MulticlassClassificationTrainers, ITrainerEstimator<BinaryPredictionTransformer<TModel>, TModel>, String, Boolean, IEstimator<ISingleFeaturePredictionTransformer<ICalibrator>>, Int32, Boolean)
- OnlineGradientDescent(RegressionTrainers, Options)
- OnlineGradientDescent(RegressionTrainers, String, String, IRegressionLoss, Single, Boolean, Single, Int32)
- PairwiseCoupling<TModel>(MulticlassClassificationTrainers, ITrainerEstimator<ISingleFeaturePredictionTransformer<TModel>, TModel>, String, Boolean, IEstimator<ISingleFeaturePredictionTransformer<ICalibrator>>, Int32)
- Prior(BinaryClassificationTrainers, String, String)
- Sdca(RegressionTrainers, Options)
- Sdca(RegressionTrainers, String, String, String, ISupportSdcaRegressionLoss, Single?, Single?, Int32?)
- SdcaLogisticRegression(BinaryClassificationTrainers, Options)
- SdcaLogisticRegression(BinaryClassificationTrainers, String, String, String, Single?, Single?, Int32?)
- SdcaMaximumEntropy(MulticlassClassificationTrainers, Options)
- SdcaMaximumEntropy(MulticlassClassificationTrainers, String, String, String, Single?, Single?, Int32?)
- SdcaNonCalibrated(BinaryClassificationTrainers, Options)
- SdcaNonCalibrated(MulticlassClassificationTrainers, Options)
- SdcaNonCalibrated(BinaryClassificationTrainers, String, String, String, ISupportSdcaClassificationLoss, Single?, Single?, Int32?)
- SdcaNonCalibrated(MulticlassClassificationTrainers, String, String, String, ISupportSdcaClassificationLoss, Single?, Single?, Int32?)
- SgdCalibrated(BinaryClassificationTrainers, Options)
- SgdCalibrated(BinaryClassificationTrainers, String, String, String, Int32, Double, Single)
- SgdNonCalibrated(BinaryClassificationTrainers, Options)
- SgdNonCalibrated(BinaryClassificationTrainers, String, String, String, IClassificationLoss, Int32, Double, Single)
net5.0
namespace Microsoft.ML
{
public static class StandardTrainersCatalog
}
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| .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 net5.0 | |
| 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