Class MinimumCardinalityDataset<T extends Output<T>>

java.lang.Object

org.tribuo.Dataset<T>

org.tribuo.ImmutableDataset<T>

org.tribuo.dataset.MinimumCardinalityDataset<T>

Type Parameters:

T - The type of the outputs in this Dataset.

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.provenance.Provenancable<DatasetProvenance>, Serializable, Iterable<Example<T>>

public class MinimumCardinalityDataset<T extends Output<T>>
extends ImmutableDataset<T>

This class creates a pruned dataset in which low frequency features that occur less than the provided minimum cardinality have been removed. This can be useful when the dataset is very large due to many low-frequency features. For example, this class can be used to remove low frequency words from a BoW formatted dataset. Here, a new dataset is created so that the feature counts are recalculated and so that the original, passed-in dataset is not modified. The returned dataset may have fewer examples because if any of the examples have no features after the minimum cardinality has been applied, then those examples will not be added to the constructed dataset.

See Also:

• Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	MinimumCardinalityDataset.MinimumCardinalityDatasetProvenance	Provenance for MinimumCardinalityDataset.

Field Summary

Fields inherited from class org.tribuo.ImmutableDataset

dropInvalidExamples, featureIDMap, outputIDInfo

Fields inherited from class org.tribuo.Dataset

data, indices, outputFactory, sourceProvenance

Constructor Summary

Constructors

Constructor	Description
MinimumCardinalityDataset(Dataset<T> dataset, int minCardinality)

Method Summary

Modifier and Type	Method	Description
int	getMinCardinality()	The minimum cardinality threshold for the features.
int	getNumExamplesRemoved()	The number of examples removed due to a lack of features.
DatasetProvenance	getProvenance()
Set<String>	getRemoved()	The feature names that were removed.

Methods inherited from class org.tribuo.ImmutableDataset

add, add, copyDataset, copyDataset, copyDataset, getDropInvalidExamples, getFeatureIDMap, getFeatureMap, getOutputIDInfo, getOutputInfo, getOutputs, hashFeatureMap, toString

Methods inherited from class org.tribuo.Dataset

createTransformers, createTransformers, getData, getExample, getOutputFactory, getSourceDescription, getSourceProvenance, iterator, shuffle, size

Methods inherited from class java.lang.Object

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

Methods inherited from interface java.lang.Iterable

forEach, spliterator

Constructor Details

MinimumCardinalityDataset

public MinimumCardinalityDataset(Dataset<T> dataset,
 int minCardinality)

Parameters:

dataset - this dataset is left untouched and is used to populate the constructed dataset.

minCardinality - features with a frequency less than minCardinality will be removed.

Method Details

getRemoved

public Set<String> getRemoved()

The feature names that were removed.

Returns:

The feature names.

getNumExamplesRemoved

public int getNumExamplesRemoved()

The number of examples removed due to a lack of features.

Returns:

The number of removed examples.

getMinCardinality

public int getMinCardinality()

The minimum cardinality threshold for the features.

Returns:

The cardinality threshold.

getProvenance

public DatasetProvenance getProvenance()

Specified by:

getProvenance in interface com.oracle.labs.mlrg.olcut.provenance.Provenancable<T extends Output<T>>

Overrides:

getProvenance in class ImmutableDataset<T extends Output<T>>