ITrainerEstimator<TTransformer,TModel> Interface

  • Reference

Definition

Namespace:
Microsoft.ML.Trainers
Assembly:
Microsoft.ML.Data.dll
Package:
Microsoft.ML v3.0.1
Package:
Microsoft.ML v1.0.0
Package:
Microsoft.ML v1.1.0
Package:
Microsoft.ML v1.2.0
Package:
Microsoft.ML v1.3.1
Package:
Microsoft.ML v1.4.0
Package:
Microsoft.ML v1.5.5
Package:
Microsoft.ML v1.6.0
Package:
Microsoft.ML v1.7.0
Package:
Microsoft.ML v2.0.0

Interface for the Trainer Estimator.

public interface ITrainerEstimator<out TTransformer,out TModel> : Microsoft.ML.IEstimator<out TTransformer> where TTransformer : IPredictionTransformer<out TModel> where TModel : class
public interface ITrainerEstimator<out TTransformer,out TModel> : Microsoft.ML.IEstimator<out TTransformer> where TTransformer : ISingleFeaturePredictionTransformer<out TModel> where TModel : class
type ITrainerEstimator<'ransformer, 'Model (requires 'ransformer :> IPredictionTransformer<'Model> and 'Model : null)> = interface
    interface IEstimator<'ransformer (requires 'ransformer :> IPredictionTransformer<'Model>)>
type ITrainerEstimator<'ransformer, 'Model (requires 'ransformer :> ISingleFeaturePredictionTransformer<'Model> and 'Model : null)> = interface
    interface IEstimator<'ransformer (requires 'ransformer :> ISingleFeaturePredictionTransformer<'Model>)>
Public Interface ITrainerEstimator(Of Out TTransformer, Out TModel)
Implements IEstimator(Of Out TTransformer)

Type Parameters

TTransformer

The type of the transformer returned by the estimator.

This type parameter is covariant. That is, you can use either the type you specified or any type that is more derived. For more information about covariance and contravariance, see Covariance and Contravariance in Generics.
TModel

The type of the model parameters.

This type parameter is covariant. That is, you can use either the type you specified or any type that is more derived. For more information about covariance and contravariance, see Covariance and Contravariance in Generics.
Derived
Implements
IEstimator<TTransformer>

Properties

Info

Gets the TrainerInfo information about the trainer.

Methods

Fit(IDataView)

Train and return a transformer.

(Inherited from IEstimator<TTransformer>)
GetOutputSchema(SchemaShape)

Schema propagation for estimators. Returns the output schema shape of the estimator, if the input schema shape is like the one provided.

(Inherited from IEstimator<TTransformer>)

Extension Methods

AppendCacheCheckpoint<TTrans>(IEstimator<TTrans>, IHostEnvironment)

Append a 'caching checkpoint' to the estimator chain. This will ensure that the downstream estimators will be trained against cached data. It is helpful to have a caching checkpoint before trainers that take multiple data passes.
WithOnFitDelegate<TTransformer>(IEstimator<TTransformer>, Action<TTransformer>)

Given an estimator, return a wrapping object that will call a delegate once Fit(IDataView) is called. It is often important for an estimator to return information about what was fit, which is why the Fit(IDataView) method returns a specifically typed object, rather than just a general ITransformer. However, at the same time, IEstimator<TTransformer> are often formed into pipelines with many objects, so we may need to build a chain of estimators via EstimatorChain<TLastTransformer> where the estimator for which we want to get the transformer is buried somewhere in this chain. For that scenario, we can through this method attach a delegate that will be called once fit is called.

Applies to