MissingValueReplacingEstimator Class
Definition
Important
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public sealed class MissingValueReplacingEstimator : Microsoft.ML.IEstimator<Microsoft.ML.Transforms.MissingValueReplacingTransformer>type MissingValueReplacingEstimator = class
interface IEstimator<MissingValueReplacingTransformer>Public NotInheritable Class MissingValueReplacingEstimator
Implements IEstimator(Of MissingValueReplacingTransformer)- Inheritance
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MissingValueReplacingEstimator
- Implements
Remarks
Estimator Characteristics
| Does this estimator need to look at the data to train its parameters? | Yes |
| Input column data type | Vector or scalar of Single or Double |
| Output column data type | The same as the data type in the input column |
| Exportable to ONNX | Yes |
The resulting <xref:Microsoft.ML.Transforms.MissingValueReplacingTransformer"/> creates a new column, named as specified in the output column name parameters, and copies the data from the input column to this new column with exception what missing values in data would be replaced according to chosen strategy.
Check the See Also section for links of usage examples.
Methods
| Fit(IDataView) |
Trains and returns a MissingValueReplacingTransformer. |
| 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. |