Interface MultiLabelObjective

All Superinterfaces:
com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>, SGDObjective<SGDVector>
All Known Implementing Classes:
BinaryCrossEntropy, Hinge
public interface MultiLabelObjective extends SGDObjective<SGDVector>
An interface for multi-label prediction objectives.

An objective knows if it generates a probabilistic model or not, and what kind of normalization needs to be applied to produce probability values.

  • Method Summary

    Modifier and Type
    Method
    Description
    VectorNormalizer
    getNormalizer()
    Generates a new VectorNormalizer which normalizes the predictions into a suitable format.
    boolean
    isProbabilistic()
    Does the objective function score probabilities or not?
    double
    threshold()
    The default prediction threshold for creating the output.

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

    postConfig

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

    getProvenance

    Methods inherited from interface org.tribuo.common.sgd.SGDObjective

    lossAndGradient

  • Method Details

    • getNormalizer

      VectorNormalizer getNormalizer()
      Generates a new VectorNormalizer which normalizes the predictions into a suitable format.
      Returns:
      The vector normalizer for this objective.

    • isProbabilistic

      boolean isProbabilistic()
      Does the objective function score probabilities or not?
      Returns:
      boolean.

    • threshold

      double threshold()
      The default prediction threshold for creating the output.
      Returns:
      The threshold.