IPredictionTransformer<TModel> Interface

Definition

Namespace:

Microsoft.ML

Assembly:

Microsoft.ML.Data.dll

Package:

Microsoft.ML v3.0.1

An interface for all the transformer that can transform data based on the Microsoft.ML.IPredictor field. The implementations of this interface either have no feature column, or have more than one feature column, and cannot implement the ISingleFeaturePredictionTransformer<TModel>, which most of the ML.Net tranformer implement.

public interface IPredictionTransformer<out TModel> : Microsoft.ML.ITransformer where TModel : class

type IPredictionTransformer<'Model (requires 'Model : null)> = interface
    interface ITransformer
    interface ICanSaveModel

Public Interface IPredictionTransformer(Of Out TModel)
Implements ITransformer

Type Parameters

TModel

The Microsoft.ML.IPredictor or ICalibrator used for the data transformation.

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

Microsoft.ML.Calibrators.CalibratorTransformer<TICalibrator>

Microsoft.ML.Data.PredictionTransformerBase<TModel>

Microsoft.ML.Data.SingleFeaturePredictionTransformerBase<TModel>

Microsoft.ML.ISingleFeaturePredictionTransformer<TModel>

Implements

ICanSaveModel ITransformer

Properties

IsRowToRowMapper	Whether a call to GetRowToRowMapper(DataViewSchema) should succeed, on an appropriate schema. (Inherited from ITransformer)
Model

Methods

GetOutputSchema(DataViewSchema)	Schema propagation for transformers. Returns the output schema of the data, if the input schema is like the one provided. (Inherited from ITransformer)
GetRowToRowMapper(DataViewSchema)	Constructs a row-to-row mapper based on an input schema. If IsRowToRowMapper is false, then an exception should be thrown. If the input schema is in any way unsuitable for constructing the mapper, an exception should likewise be thrown. (Inherited from ITransformer)
Save(ModelSaveContext)	(Inherited from ICanSaveModel)
Transform(IDataView)	Take the data in, make transformations, output the data. Note that IDataView's are lazy, so no actual transformations happen here, just schema validation. (Inherited from ITransformer)

Extension Methods

Preview(ITransformer, IDataView, Int32)	Preview an effect of the transformer on a given data.
Append<TTrans>(ITransformer, TTrans)	Create a new transformer chain, by appending another transformer to the end of this transformer chain.
CreateTimeSeriesEngine<TSrc,TDst>(ITransformer, IHostEnvironment, PredictionEngineOptions)	TimeSeriesPredictionEngine<TSrc,TDst> creates a prediction engine for a time series pipeline. It updates the state of time series model with observations seen at prediction phase and allows checkpointing the model.
CreateTimeSeriesEngine<TSrc,TDst>(ITransformer, IHostEnvironment, Boolean, SchemaDefinition, SchemaDefinition)	TimeSeriesPredictionEngine<TSrc,TDst> creates a prediction engine for a time series pipeline. It updates the state of time series model with observations seen at prediction phase and allows checkpointing the model.