4. The non-transitory computer-readable medium of claim 1 , further comprising instructions that when executed by the processor cause the processor to: access a set of arbiter points {a 0 , . . . , a n } to perform the classification of the data point q; for each arbiter point, determine a class-aggregated similarity metric for the set of arbiter points with respect to a given arbiter point; aggregate class-aggregated similarity metrics for the first set among the arbiter points to produce a first arbiter-class-aggregated similarity metric; aggregate class-aggregated similarity metrics for the second set among the arbiter points to produce a second arbiter-class-aggregated similarity metric; and classify the query data point q based on a comparison of the first class-aggregated similarity metric and the second class-aggregated similarity metric.
4. The non-transitory computer-readable medium of claim 1 , further comprising instructions that when executed by the processor cause the processor to: access a set of arbiter points {a 0 , . . . , a n } to perform the classification of the data point q; for each arbiter point, determine a class-aggregated similarity metric for the set of arbiter points with respect to a given arbiter point; aggregate class-aggregated similarity metrics for the first set among the arbiter points to produce a first arbiter-class-aggregated similarity metric; aggregate class-aggregated similarity metrics for the second set among the arbiter points to produce a second arbiter-class-aggregated similarity metric; and classify the query data point q based on a comparison of the first class-aggregated similarity metric and the second class-aggregated similarity metric. 5. The non-transitory computer-readable medium of claim 4 , wherein the instructions further comprise instructions that when executed by the processor cause the processor to select, as the set of arbiter points, one or more data points from the first set of classified data points or from the second set of classified data points.