The transformer is a component that transforms data. It also supports 'schema propagation' to answer the question of 'how will the data with this schema look, after you transform it?'.
public interface ITransformer : Microsoft.ML.ICanSaveModel
type ITransformer = interface interface ICanSaveModel
Public Interface ITransformer Implements ICanSaveModel
Whether a call to GetRowToRowMapper(DataViewSchema) should succeed, on an appropriate schema.
Schema propagation for transformers. Returns the output schema of the data, if the input schema is like the one provided.
Constructs a row-to-row mapper based on an input schema. If IsRowToRowMapper
|Save(ModelSaveContext)||(Inherited from ICanSaveModel)|
Take the data in, make transformations, output the data. Note that IDataView's are lazy, so no actual transformations happen here, just schema validation.
|Preview(ITransformer, IDataView, Int32)||
Preview an effect of the
Create a new transformer chain, by appending another transformer to the end of this transformer chain.
|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.
|CreateTimeSeriesPredictionFunction<TSrc,TDst>(ITransformer, IHostEnvironment, Boolean, SchemaDefinition, SchemaDefinition)||
TimeSeriesPredictionFunction<TSrc,TDst> creates a prediction function/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.