org.tribuo.transform

Class TransformerMap

java.lang.Object

org.tribuo.transform.TransformerMap

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.provenance.Provenancable<TransformerMap.TransformerMapProvenance>, Serializable

public final class TransformerMap
extends Object
implements com.oracle.labs.mlrg.olcut.provenance.Provenancable<TransformerMap.TransformerMapProvenance>, Serializable

A collection of Transformers which can be applied to a Dataset or Example. A TransformerMap is created by applying a TransformationMap to a Dataset. It contains Transformers which are specific to the Dataset which created it, for example the range of a feature used in binning is fixed to the value from that Dataset.

Transformations only operate on observed values. To operate on implicit zeros then first call MutableDataset.densify() on the datasets.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	TransformerMap.TransformerMapProvenance Provenance for TransformerMap.

Constructor Summary

Constructors

Constructor and Description
TransformerMap(Map<String,List<Transformer>> map, DatasetProvenance datasetProvenance, com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance transformationMapProvenance) Constructs a transformer map which encapsulates a set of transformers that can be applied to features.

Method Summary

Modifier and Type	Method and Description
static double	applyTransformerList(double value, List<Transformer> transformerList) Applies a List of Transformers to the supplied double value, returning the transformed value.
Set<Map.Entry<String,List<Transformer>>>	entrySet() Get the feature names and associated list of transformers.
TransformerMap.TransformerMapProvenance	getProvenance()
String	toString()
<T extends Output<T>> MutableDataset<T>	transformDataset(Dataset<T> dataset) Copies the supplied dataset and applies the transformers to each example in it.
<T extends Output<T>> MutableDataset<T>	transformDataset(Dataset<T> dataset, boolean densify) Copies the supplied dataset and applies the transformers to each example in it.
<T extends Output<T>> Example<T>	transformExample(Example<T> example) Copies the supplied example and applies the transformers to it.
<T extends Output<T>> Example<T>	transformExample(Example<T> example, List<String> featureNames) Copies the supplied example and applies the transformers to it.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

TransformerMap

public TransformerMap(Map<String,List<Transformer>> map,
                      DatasetProvenance datasetProvenance,
                      com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance transformationMapProvenance)

Constructs a transformer map which encapsulates a set of transformers that can be applied to features.

Parameters:

map - The transformers, one per transformed feature.

datasetProvenance - The provenance of the dataset the transformers were fit against.

transformationMapProvenance - The provenance of the transformation map that was fit.

Method Detail

applyTransformerList

public static double applyTransformerList(double value,
                                          List<Transformer> transformerList)

Applies a List of Transformers to the supplied double value, returning the transformed value.

Parameters:

value - The value to transform.

transformerList - The transformers to apply.

Returns:

The transformed value.

transformExample

public <T extends Output<T>> Example<T> transformExample(Example<T> example)

Copies the supplied example and applies the transformers to it.

Type Parameters:

T - The type of Output.

Parameters:

example - The example to transform.

Returns:

A copy of the example with the transformers applied to it's features.

transformExample

public <T extends Output<T>> Example<T> transformExample(Example<T> example,
                                                         List<String> featureNames)

Copies the supplied example and applies the transformers to it.

Type Parameters:

T - The type of Output.

Parameters:

example - The example to transform.

featureNames - The feature names to densify.

Returns:

A copy of the example with the transformers applied to it's features.

transformDataset

public <T extends Output<T>> MutableDataset<T> transformDataset(Dataset<T> dataset)

Copies the supplied dataset and applies the transformers to each example in it.

Does not densify the dataset first.

Type Parameters:

T - The type of Output.

Parameters:

dataset - The dataset to transform.

Returns:

A deep copy of the dataset (and it's examples) with the transformers applied to it's features.

transformDataset

public <T extends Output<T>> MutableDataset<T> transformDataset(Dataset<T> dataset,
                                                                boolean densify)

Copies the supplied dataset and applies the transformers to each example in it.

Type Parameters:

T - The type of Output.

Parameters:

dataset - The dataset to transform.

densify - Densify the dataset before transforming it.

Returns:

A deep copy of the dataset (and it's examples) with the transformers applied to it's features.

toString

public String toString()

Overrides:

toString in class Object

entrySet

public Set<Map.Entry<String,List<Transformer>>> entrySet()

Get the feature names and associated list of transformers.

Returns:

The entry set of the transformer map.

getProvenance

public TransformerMap.TransformerMapProvenance getProvenance()

Specified by:

getProvenance in interface com.oracle.labs.mlrg.olcut.provenance.Provenancable<TransformerMap.TransformerMapProvenance>