TrainerEstimatorBaseWithGroupId<TTransformer,TModel> Class

Definition

Namespace:

Microsoft.ML.Trainers

Assembly:

Microsoft.ML.Data.dll

Package:

Microsoft.ML v3.0.1

This represents a basic class for 'simple trainer'. A 'simple trainer' accepts one feature column and one label column, also optionally a weight column. It produces a 'prediction transformer'.

public abstract class TrainerEstimatorBaseWithGroupId<TTransformer,TModel> : Microsoft.ML.Trainers.TrainerEstimatorBase<TTransformer,TModel> where TTransformer : ISingleFeaturePredictionTransformer<TModel> where TModel : class

type TrainerEstimatorBaseWithGroupId<'ransformer, 'Model (requires 'ransformer :> ISingleFeaturePredictionTransformer<'Model> and 'Model : null)> = class
    inherit TrainerEstimatorBase<'ransformer, 'Model (requires 'ransformer :> ISingleFeaturePredictionTransformer<'Model> and 'Model : null)>

Public MustInherit Class TrainerEstimatorBaseWithGroupId(Of TTransformer, TModel)
Inherits TrainerEstimatorBase(Of TTransformer, TModel)

Type Parameters

TTransformer

TModel

Inheritance

Object

TrainerEstimatorBase<TTransformer,TModel>

TrainerEstimatorBaseWithGroupId<TTransformer,TModel>

Derived

Microsoft.ML.Trainers.FastTree.FastTreeTrainerBase<TOptions,TTransformer,TModel>

Microsoft.ML.Trainers.LightGbm.LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>

Fields

FeatureColumn	The feature column that the trainer expects. (Inherited from TrainerEstimatorBase<TTransformer,TModel>)
GroupIdColumn	The optional groupID column that the ranking trainers expects.
LabelColumn	The label column that the trainer expects. Can be null, which indicates that label is not used for training. (Inherited from TrainerEstimatorBase<TTransformer,TModel>)
WeightColumn	The weight column that the trainer expects. Can be null, which indicates that weight is not used for training. (Inherited from TrainerEstimatorBase<TTransformer,TModel>)

Properties

Info	The information about the trainer: whether it benefits from normalization, caching etc. (Inherited from TrainerEstimatorBase<TTransformer,TModel>)

Methods

Fit(IDataView)	Trains and returns a ITransformer. (Inherited from TrainerEstimatorBase<TTransformer,TModel>)
GetOutputSchema(SchemaShape)	(Inherited from TrainerEstimatorBase<TTransformer,TModel>)

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.