Class ConfidenceIntervalClusteringBasedActiveDyadRanker


  • public class ConfidenceIntervalClusteringBasedActiveDyadRanker
    extends ARandomlyInitializingDyadRanker
    A prototypical active dyad ranker based on clustering of pseudo confidence intervals. During the learning procedure, it keeps track over the standard deviation of the skill values predicted for a dyad. First a constant number of random queries is sampled at the beginning. Then the sampling strategy clusteres the skill values of all alternatives for each instance according to the lower and upper bounds of the confidence intervals of the skill for all corresponding dyads. Confidence intervals are given by [skill - std, skill + std] where skill denotes the skill and std denotes the empirical standard deviaition of the skill for a dyad. Afterwards, it picks one of the largest clusters and then selects the two dyads for which the confidence intervals overlap the most within the cluster for pairwise comparison, until a minibatch of constant size is filled.