Package ai.libs.jaicore.ml.ranking.dyad.learner.optimizing

Interface IDyadRankingFeatureTransformPLGradientFunction

  • All Superinterfaces:
    ai.libs.jaicore.math.gradientdescent.IGradientFunction
    All Known Implementing Classes:
    DyadRankingFeatureTransformNegativeLogLikelihoodDerivative
    public interface IDyadRankingFeatureTransformPLGradientFunction
extends ai.libs.jaicore.math.gradientdescent.IGradientFunction
    Represents a differentiable function in the context of dyad ranking based on feature transformation Placket-Luce models.

    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method Description
      void initialize​(org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset dataset, java.util.Map<org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance,​java.util.Map<org.api4.java.ai.ml.ranking.dyad.dataset.IDyad,​org.api4.java.common.math.IVector>> featureTransforms)
      Initialize the function with the given data set and feature transformation method.

      • Methods inherited from interface ai.libs.jaicore.math.gradientdescent.IGradientFunction

        apply

    • Method Detail

      • initialize

        void initialize​(org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset dataset,
                java.util.Map<org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance,​java.util.Map<org.api4.java.ai.ml.ranking.dyad.dataset.IDyad,​org.api4.java.common.math.IVector>> featureTransforms)
        Initialize the function with the given data set and feature transformation method.
        Parameters:
        dataset - the dataset to use
        featureTransforms - the pre computed feature transformations