public class SquaredLoss extends Object implements RegressionObjective
Constructor and Description |
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SquaredLoss()
Constructs a SquaredLoss.
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Modifier and Type | Method and Description |
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com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance |
getProvenance() |
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> |
loss(DenseVector truth,
SGDVector prediction)
Deprecated.
|
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> |
lossAndGradient(DenseVector truth,
SGDVector prediction)
Scores a prediction, returning the loss and a vector of per output dimension gradients.
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String |
toString() |
@Deprecated public com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> loss(DenseVector truth, SGDVector prediction)
RegressionObjective
loss
in interface RegressionObjective
truth
- The true regression value.prediction
- The predicted regression value.public com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> lossAndGradient(DenseVector truth, SGDVector prediction)
SGDObjective
lossAndGradient
in interface SGDObjective<DenseVector>
lossAndGradient
in interface RegressionObjective
truth
- The true output.prediction
- The prediction for each dimension.public com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance getProvenance()
getProvenance
in interface com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
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