IEstimator<TTransformer> IEstimator<TTransformer> IEstimator<TTransformer> Interface

Definition

The estimator (in Spark terminology) is an 'untrained transformer'. It needs to 'fit' on the data to manufacture a transformer. It also provides the 'schema propagation' like transformers do, but over SchemaShape instead of DataViewSchema.

public interface IEstimator<out TTransformer> where TTransformer : ITransformer
type IEstimator<'ransformer (requires 'ransformer :> ITransformer)> = interface
Public Interface IEstimator(Of Out TTransformer)

Type Parameters

TTransformer
Derived

Methods

Fit(IDataView) Fit(IDataView) Fit(IDataView)

Train and return a transformer.

GetOutputSchema(SchemaShape) GetOutputSchema(SchemaShape) GetOutputSchema(SchemaShape)

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

Extension Methods

WithOnFitDelegate<TTransformer>(IEstimator<TTransformer>, Action<TTransformer>) WithOnFitDelegate<TTransformer>(IEstimator<TTransformer>, Action<TTransformer>) 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