# TrivialEstimator<TTransformer> Class

## Definition

The trivial implementation of IEstimator<TTransformer> that already has the transformer and returns it on every call to Fit(IDataView).

Concrete implementations still have to provide the schema propagation mechanism, since there is no easy way to infer it from the transformer.

public abstract class TrivialEstimator<TTransformer> : Microsoft.ML.IEstimator<TTransformer> where TTransformer : class, ITransformer
type TrivialEstimator<'ransformer (requires 'ransformer : null and 'ransformer :> ITransformer)> = class
interface IEstimator<'ransformer (requires 'ransformer : null and 'ransformer :> ITransformer)>
Public MustInherit Class TrivialEstimator(Of TTransformer)
Implements IEstimator(Of TTransformer)

#### Type Parameters

TTransformer
Inheritance
TrivialEstimator<TTransformer>
Derived
Implements

## Extension Methods

 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 are often formed into pipelines with many objects, so we may need to build a chain of estimators via EstimatorChain 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.