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.