Active learning performance for different model designs.

Performance was measured as the difference in the number of batches to achieve (A,B) 100% or (C,D) 90% accuracy between active and random learning. (A,C) Greedy Merge, (B,D) B-Clustering. Warmer colors indicate greater experiment savings with an active learner.