ColumnSelectingTransformer Class

Definition

Namespace:

Microsoft.ML.Transforms

Assembly:

Microsoft.ML.Data.dll

Package:

Microsoft.ML v3.0.1

ITransformer resulting from fitting an ColumnSelectingEstimator.

public sealed class ColumnSelectingTransformer : Microsoft.ML.ITransformer

type ColumnSelectingTransformer = class
    interface ITransformer
    interface ICanSaveModel

Public NotInheritable Class ColumnSelectingTransformer
Implements ITransformer

Inheritance

Object

ColumnSelectingTransformer

Implements

ICanSaveModel ITransformer

Methods

GetOutputSchema(DataViewSchema)	Schema propagation for transformers. Returns the output schema of the data, if the input schema is like the one provided.
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.

Explicit Interface Implementations

ICanSaveModel.Save(ModelSaveContext)
ITransformer.GetRowToRowMapper(DataViewSchema)	Constructs a row-to-row mapper based on an input schema. If IsRowToRowMapper is false, then an exception is thrown. If the input schema is in any way unsuitable for constructing the mapper, an exception should likewise be thrown.
ITransformer.IsRowToRowMapper

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.