MulticlassClassificationTrainers
LbfgsMaximumEntropy(MulticlassClassificationTrainers, Options)- LbfgsMaximumEntropy(MulticlassClassificationTrainers, String, String, String, Single, Single, Single, Int32, Boolean)
- LbfgsMaximumEntropy<TVal>(MulticlassClassificationTrainers, Key<UInt32, TVal>, Vector<Single>, Scalar<Single>, Options, Action<MaximumEntropyModelParameters>)
- LbfgsMaximumEntropy<TVal>(MulticlassClassificationTrainers, Key<UInt32, TVal>, Vector<Single>, Scalar<Single>, Single, Single, Single, Int32, Boolean, Action<MaximumEntropyModelParameters>)
- LightGbm(MulticlassClassificationTrainers, Options)
- LightGbm(MulticlassClassificationTrainers, Stream, String)
- LightGbm(MulticlassClassificationTrainers, String, String, String, Int32?, Int32?, Double?, Int32)
- MulticlassNaiveBayesTrainer<TVal>(MulticlassClassificationTrainers, Key<UInt32, TVal>, Vector<Single>, Action<NaiveBayesMulticlassModelParameters>)
- NaiveBayes(MulticlassClassificationTrainers, String, String)
- NamedEntityRecognition(MulticlassClassificationTrainers, NerOptions)
- NamedEntityRecognition(MulticlassClassificationTrainers, String, String, String, Int32, Int32, BertArchitecture, IDataView)
- NameEntityRecognition(MulticlassClassificationTrainers, NerOptions)
- NameEntityRecognition(MulticlassClassificationTrainers, String, String, String, Int32, Int32, BertArchitecture, IDataView)
- ObjectDetection(MulticlassClassificationTrainers, Options)
- ObjectDetection(MulticlassClassificationTrainers, String, String, String, String, String, String, Int32)
- OneVersusAll<TModel>(MulticlassClassificationTrainers, ITrainerEstimator<BinaryPredictionTransformer<TModel>, TModel>, String, Boolean, IEstimator<ISingleFeaturePredictionTransformer<ICalibrator>>, Int32, Boolean)
- PairwiseCoupling<TModel>(MulticlassClassificationTrainers, ITrainerEstimator<ISingleFeaturePredictionTransformer<TModel>, TModel>, String, Boolean, IEstimator<ISingleFeaturePredictionTransformer<ICalibrator>>, Int32)
- QuestionAnswer(MulticlassClassificationTrainers, Options)
- QuestionAnswer(MulticlassClassificationTrainers, String, String, String, String, String, String, Int32, Int32, Int32, BertArchitecture, IDataView)
- Sdca<TVal>(MulticlassClassificationTrainers, Key<UInt32, TVal>, Vector<Single>, Scalar<Single>, Options, Action<MaximumEntropyModelParameters>)
- Sdca<TVal>(MulticlassClassificationTrainers, Key<UInt32, TVal>, Vector<Single>, Scalar<Single>, Nullable<Single>, Nullable<Single>, Nullable<Int32>, Action<MaximumEntropyModelParameters>)
- SdcaMaximumEntropy(MulticlassClassificationTrainers, Options)
- SdcaMaximumEntropy(MulticlassClassificationTrainers, String, String, String, Single?, Single?, Int32?)
- SdcaNonCalibrated(MulticlassClassificationTrainers, Options)
- SdcaNonCalibrated(MulticlassClassificationTrainers, String, String, String, ISupportSdcaClassificationLoss, Single?, Single?, Int32?)
- SdcaNonCalibrated<TVal>(MulticlassClassificationTrainers, Key<UInt32, TVal>, Vector<Single>, Scalar<Single>, Options, Action<LinearMulticlassModelParameters>)
- SdcaNonCalibrated<TVal>(MulticlassClassificationTrainers, Key<UInt32, TVal>, Vector<Single>, ISupportSdcaClassificationLoss, Scalar<Single>, Nullable<Single>, Nullable<Single>, Nullable<Int32>, Action<LinearMulticlassModelParameters>)
- TextClassification(MulticlassClassificationTrainers, TextClassificationOptions)
- TextClassification(MulticlassClassificationTrainers, String, String, String, String, String, Int32, Int32, BertArchitecture, IDataView)
net462
namespace Microsoft.ML
{
public static class StandardTrainersCatalog
{
public static NaiveBayesMulticlassTrainer NaiveBayes(this MulticlassClassificationTrainers catalog, string labelColumnName = "Label", string featureColumnName = "Features");
}
}
| nuget.org | 0.0 %
Reference this API |
|---|---|
| .NET | 5.06.07.08.09.0 |
| .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 net462 | |
| Assembly | Microsoft.ML.StandardTrainers , Version=1.0.0.0, PublicKeyToken=cc7b13ffcd2ddd51 |
| Referencing | Your project needs a package reference to |
| Package | Microsoft.ML (4.0.0) netstandard2.0 |
| Platform Restrictions | This framework does not have platform annotations. |
- Built-in API
- Package-provided API