Interface RegressionObjective

All Superinterfaces:
com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
All Known Implementing Classes:
AbsoluteLoss, Huber, SquaredLoss
public interface RegressionObjective extends com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
An interface for regression objectives.

  • Method Summary

    Modifier and Type
    Method
    Description
    com.oracle.labs.mlrg.olcut.util.Pair<Double, SGDVector>
    loss(DenseVector truth, SGDVector prediction)
    Scores a prediction, returning the loss.

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

    postConfig

    Methods inherited from interface com.oracle.labs.mlrg.olcut.provenance.Provenancable

    getProvenance

  • Method Details

    • loss

      com.oracle.labs.mlrg.olcut.util.Pair<Double, SGDVector> loss(DenseVector truth, SGDVector prediction)
      Scores a prediction, returning the loss.
      Parameters:
      truth - The true regression value.
      prediction - The predicted regression value.
      Returns:
      A pair with the loss and gradient.