Class Huber
java.lang.Object
org.tribuo.regression.sgd.objectives.Huber
- All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.config.Configurable,com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>,SGDObjective<DenseVector>,RegressionObjective
Huber loss, i.e., a mixture of l2 and l1 losses.
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Field Summary
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Constructor Summary
ConstructorsConstructorDescriptionHuber()Huber Loss using the default costDEFAULT_COST.Huber(double cost) Huber loss using the supplied cost. -
Method Summary
Modifier and TypeMethodDescriptioncom.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenanceloss(DenseVector truth, SGDVector prediction) Deprecated.lossAndGradient(DenseVector truth, SGDVector prediction) Scores a prediction, returning the loss and a vector of per output dimension gradients.voidUsed by the OLCUT configuration system, and should not be called by external code.toString()
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Field Details
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DEFAULT_COST
public static final double DEFAULT_COST- See Also:
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Constructor Details
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Huber
public Huber()Huber Loss using the default costDEFAULT_COST. -
Huber
public Huber(double cost) Huber loss using the supplied cost. Cost must be positive.- Parameters:
cost- The cost.
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Method Details
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postConfig
public void postConfig()Used by the OLCUT configuration system, and should not be called by external code.- Specified by:
postConfigin interfacecom.oracle.labs.mlrg.olcut.config.Configurable
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loss
@Deprecated public com.oracle.labs.mlrg.olcut.util.Pair<Double, SGDVector> loss(DenseVector truth, SGDVector prediction) Deprecated.Description copied from interface:RegressionObjectiveScores a prediction, returning the loss.- Specified by:
lossin interfaceRegressionObjective- Parameters:
truth- The true regression value.prediction- The predicted regression value.- Returns:
- A pair with the loss and gradient.
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lossAndGradient
public com.oracle.labs.mlrg.olcut.util.Pair<Double, SGDVector> lossAndGradient(DenseVector truth, SGDVector prediction) Description copied from interface:SGDObjectiveScores a prediction, returning the loss and a vector of per output dimension gradients.- Specified by:
lossAndGradientin interfaceRegressionObjective- Specified by:
lossAndGradientin interfaceSGDObjective<DenseVector>- Parameters:
truth- The true output.prediction- The prediction for each dimension.- Returns:
- The score and per dimension gradient.
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toString
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getProvenance
public com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance getProvenance()- Specified by:
getProvenancein interfacecom.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
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