Class RegressionFactory

java.lang.Object

org.tribuo.regression.RegressionFactory

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<OutputFactoryProvenance>, Serializable, OutputFactory<Regressor>

public final class RegressionFactory
extends Object
implements OutputFactory<Regressor>

A factory for creating Regressors and RegressionInfos.

It parses the regression dimensions by toStringing the input and calling Regressor.parseString(java.lang.String), unless the input is a collection, in which case it extracts the elements.

This OutputFactory has mutable state, namely the character which the dimension input is split on. In most cases the default DEFAULT_SPLIT_CHAR is fine.

See Also:

• Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static final class	RegressionFactory.RegressionFactoryProvenance	Provenance for RegressionFactory.

Field Summary

Fields

Modifier and Type	Field	Description
static final char	DEFAULT_SPLIT_CHAR
static final Regressor	UNKNOWN_MULTIPLE_REGRESSOR
static final Regressor	UNKNOWN_REGRESSOR

Constructor Summary

Constructors

Constructor	Description
RegressionFactory()	Builds a regression factory using the default split character DEFAULT_SPLIT_CHAR.
RegressionFactory(char splitChar)	Sets the split character used to parse Regressor instances from Strings.

Method Summary

Modifier and Type	Method	Description
ImmutableOutputInfo<Regressor>	constructInfoForExternalModel(Map<Regressor, Integer> mapping)	Creates an ImmutableOutputInfo from the supplied mapping.
boolean	equals(Object obj)
MutableOutputInfo<Regressor>	generateInfo()	Generates the appropriate MutableOutputInfo so the output values can be tracked by a Dataset or other aggregate.
<V> Regressor	generateOutput(V label)	Parses the MultipleRegression value either by toStringing the input and calling Regressor.parseString(java.lang.String) or if it's a collection iterating over the elements calling toString on each element in turn and using Regressor.parseElement(int, java.lang.String).
Evaluator<Regressor, RegressionEvaluation>	getEvaluator()	Gets an Evaluator suitable for measuring performance of predictions for the Output subclass.
OutputFactoryProvenance	getProvenance()
Regressor	getUnknownOutput()	Returns the singleton unknown output of type T which can be used for prediction time examples.
int	hashCode()
void	postConfig()	Used by the OLCUT configuration system, and should not be called by external code.

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.tribuo.OutputFactory

generateOutputs

Field Details

DEFAULT_SPLIT_CHAR

public static final char DEFAULT_SPLIT_CHAR

See Also:

• Constant Field Values

UNKNOWN_REGRESSOR

public static final Regressor UNKNOWN_REGRESSOR

UNKNOWN_MULTIPLE_REGRESSOR

public static final Regressor UNKNOWN_MULTIPLE_REGRESSOR

Constructor Details

RegressionFactory

public RegressionFactory()

Builds a regression factory using the default split character DEFAULT_SPLIT_CHAR.

RegressionFactory

public RegressionFactory(char splitChar)

Sets the split character used to parse Regressor instances from Strings.

Parameters:

splitChar - The split character.

Method Details

postConfig

public void postConfig()

Used by the OLCUT configuration system, and should not be called by external code.

Specified by:

postConfig in interface com.oracle.labs.mlrg.olcut.config.Configurable

generateOutput

public <V> Regressor generateOutput(V label)

Parses the MultipleRegression value either by toStringing the input and calling Regressor.parseString(java.lang.String) or if it's a collection iterating over the elements calling toString on each element in turn and using Regressor.parseElement(int, java.lang.String).

Specified by:

generateOutput in interface OutputFactory<Regressor>

Type Parameters:

V - The type of the input value.

Parameters:

label - An input value.

Returns:

A MultipleRegressor with sentinel variances.

getUnknownOutput

public Regressor getUnknownOutput()

Description copied from interface: OutputFactory

Returns the singleton unknown output of type T which can be used for prediction time examples.

Specified by:

getUnknownOutput in interface OutputFactory<Regressor>

Returns:

An unknown output.

generateInfo

public MutableOutputInfo<Regressor> generateInfo()

Description copied from interface: OutputFactory

Generates the appropriate MutableOutputInfo so the output values can be tracked by a Dataset or other aggregate.

Specified by:

generateInfo in interface OutputFactory<Regressor>

Returns:

The appropriate subclass of MutableOutputInfo initialised to zero.

constructInfoForExternalModel

public ImmutableOutputInfo<Regressor> constructInfoForExternalModel(Map<Regressor, Integer> mapping)

Description copied from interface: OutputFactory

Creates an ImmutableOutputInfo from the supplied mapping. Requires that the mapping is dense in the integers [0,mapping.size()) and each mapping is unique.

This call is used to import external models, and should not be used for other purposes.

Specified by:

constructInfoForExternalModel in interface OutputFactory<Regressor>

Parameters:

mapping - The mapping to use.

Returns:

The appropriate subclass of ImmutableOutputInfo with a single observation of each element.

getEvaluator

public Evaluator<Regressor, RegressionEvaluation> getEvaluator()

Description copied from interface: OutputFactory

Gets an Evaluator suitable for measuring performance of predictions for the Output subclass.

Evaluator instances are thread safe and immutable, and commonly this is a singleton stored in the OutputFactory implementation.

Specified by:

getEvaluator in interface OutputFactory<Regressor>

Returns:

An evaluator.

hashCode

public int hashCode()

Overrides:

hashCode in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

getProvenance

public OutputFactoryProvenance getProvenance()

Specified by:

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