org.tribuo.classification.sgd.objectives

Class Hinge

java.lang.Object

org.tribuo.classification.sgd.objectives.Hinge

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>, LabelObjective

public class Hinge
extends Object
implements LabelObjective

Hinge loss, scores the correct value margin and any incorrect predictions -margin. By default the margin is 1.0.

The Hinge loss does not generate a probabilistic model, and uses a NoopNormalizer.

Constructor Summary

Constructors

Constructor and Description
Hinge() Construct a hinge objective with a margin of 1.0.
Hinge(double margin) Construct a hinge objective with the supplied margin.

Method Summary

Modifier and Type	Method and Description
VectorNormalizer	getNormalizer() Returns a new NoopNormalizer.
com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance	getProvenance()
boolean	isProbabilistic() Returns false.
String	toString()
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	valueAndGradient(int truth, SGDVector prediction) Returns a Pair of Double and SparseVector.

Methods inherited from class java.lang.Object

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

Methods inherited from interface com.oracle.labs.mlrg.olcut.config.Configurable

postConfig

Constructor Detail

Hinge

public Hinge(double margin)

Construct a hinge objective with the supplied margin.

Parameters:

margin - The margin to use.

Hinge

public Hinge()

Construct a hinge objective with a margin of 1.0.

Method Detail

valueAndGradient

public com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> valueAndGradient(int truth,
                                                                               SGDVector prediction)

Returns a Pair of Double and SparseVector.

Specified by:

valueAndGradient in interface LabelObjective

Parameters:

truth - The true label id.

prediction - The prediction for each label id.

Returns:

The loss and per label gradient.

getNormalizer

public VectorNormalizer getNormalizer()

Returns a new NoopNormalizer.

Specified by:

getNormalizer in interface LabelObjective

Returns:

The vector normalizer.

isProbabilistic

public boolean isProbabilistic()

Returns false.

Specified by:

isProbabilistic in interface LabelObjective

Returns:

False.

toString

public String toString()

Overrides:

toString in class Object

getProvenance

public com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance getProvenance()

Specified by:

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