KeyToVectorMappingEstimator Class
Definition
Important
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Estimator for KeyToVectorMappingTransformer. Maps the value of a key into a known-sized vector of Single.
public sealed class KeyToVectorMappingEstimator : Microsoft.ML.Data.TrivialEstimator<Microsoft.ML.Transforms.KeyToVectorMappingTransformer>type KeyToVectorMappingEstimator = class
inherit TrivialEstimator<KeyToVectorMappingTransformer>Public NotInheritable Class KeyToVectorMappingEstimator
Inherits TrivialEstimator(Of KeyToVectorMappingTransformer)- Inheritance
Remarks
Estimator Characteristics
| Does this estimator need to look at the data to train its parameters? | No |
| Input column data type | Scalar or known-size vector of key type. |
| Output column data type | A known-size vector of System.Single. |
| Exportable to ONNX | Yes |
It iterates over keys in data, and for each key it produces vector of key cardinality filled with zeros except position of key value in which it put's 1.0.
For vector of keys it can either produce vector of counts for each key or concatenate them together into one vector.
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. |