KeyToValueMappingEstimator Class

  • Reference

Definition

Namespace:
Microsoft.ML.Transforms
Assembly:
Microsoft.ML.Data.dll
Package:
Microsoft.ML v3.0.1
Package:
Microsoft.ML v1.0.0
Package:
Microsoft.ML v1.1.0
Package:
Microsoft.ML v1.2.0
Package:
Microsoft.ML v1.3.1
Package:
Microsoft.ML v1.4.0
Package:
Microsoft.ML v1.5.5
Package:
Microsoft.ML v1.6.0
Package:
Microsoft.ML v1.7.0
Package:
Microsoft.ML v2.0.0

Estimator for KeyToValueMappingTransformer. Converts the key types back to their original values.

public sealed class KeyToValueMappingEstimator : Microsoft.ML.Data.TrivialEstimator<Microsoft.ML.Transforms.KeyToValueMappingTransformer>
type KeyToValueMappingEstimator = class
    inherit TrivialEstimator<KeyToValueMappingTransformer>
Public NotInheritable Class KeyToValueMappingEstimator
Inherits TrivialEstimator(Of KeyToValueMappingTransformer)
Inheritance
Object
TrivialEstimator<KeyToValueMappingTransformer>
KeyToValueMappingEstimator

Remarks

Estimator Characteristics
Does this estimator need to look at the data to train its parameters? No
Input column data type key type.
Output column data type Type of the original data, prior to converting to key type.
Exportable to ONNX Yes

Check the See Also section for links to usage examples.

Methods

Fit(IDataView) (Inherited from TrivialEstimator<TTransformer>)
GetOutputSchema(SchemaShape)

Returns the SchemaShape of the schema which will be produced by the transformer. Used for schema propagation and verification in a pipeline.

Extension Methods

AppendCacheCheckpoint<TTrans>(IEstimator<TTrans>, IHostEnvironment)

Append a 'caching checkpoint' to the estimator chain. This will ensure that the downstream estimators will be trained against cached data. It is helpful to have a caching checkpoint before trainers that take multiple data passes.
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

See also