Package es.uam.eps.ir.relison.grid.links.prediction.metrics

Interface LinkPredictionMetricConfigurator<U,​F>

Type Parameters:
U - type of the users.
F - type of the features.
All Known Implementing Classes:
AccuracyConfigurator, AUCConfigurator, F1ScoreConfigurator, PrecisionConfigurator, RecallConfigurator
public interface LinkPredictionMetricConfigurator<U,​F>
Class for configuring a given link prediction metric.

  • Method Summary

    Modifier and Type Method Description
    java.util.Map<java.lang.String,​LinkPredictionMetricFunction<U,​F>> grid​(Grid grid)
    Obtains the different link prediction metrics to compute in a grid.
    java.util.Map<java.lang.String,​java.util.function.Supplier<LinkPredictionMetric<U>>> grid​(Grid grid, Graph<U> trainGraph, Graph<U> testGraph, es.uam.eps.ir.ranksys.core.preference.PreferenceData<U,​U> trainData, es.uam.eps.ir.ranksys.core.preference.PreferenceData<U,​U> testData, es.uam.eps.ir.ranksys.core.feature.FeatureData<U,​F,​java.lang.Double> featureData, Communities<U> comms)
    Obtains the different link prediction metrics to compute in a grid.

  • Method Details

    • grid

      java.util.Map<java.lang.String,​LinkPredictionMetricFunction<U,​F>> grid​(Grid grid)
      Obtains the different link prediction metrics to compute in a grid.
      Parameters:
      grid - the grid for the link prediction metric.
      Returns:
      a map containing the different link prediction metrics.

    • grid

      java.util.Map<java.lang.String,​java.util.function.Supplier<LinkPredictionMetric<U>>> grid​(Grid grid, Graph<U> trainGraph, Graph<U> testGraph, es.uam.eps.ir.ranksys.core.preference.PreferenceData<U,​U> trainData, es.uam.eps.ir.ranksys.core.preference.PreferenceData<U,​U> testData, es.uam.eps.ir.ranksys.core.feature.FeatureData<U,​F,​java.lang.Double> featureData, Communities<U> comms)
      Obtains the different link prediction metrics to compute in a grid.
      Parameters:
      grid - the grid containing the different parameters for the metric.
      trainGraph - the training network.
      testGraph - the test network.
      trainData - the training preference data.
      testData - the test preference data.
      featureData - the feature data.
      comms - the communities for the users in the network.
      Returns:
      a map containing the different link prediction metrics.