Epsilon focusing—A strategy for active example selection

摘要

In most classical formulations of learning from examples. a passive learner is presented with examples randomly drawn. Here we discuss an ϵ-focusing strategy that actively chooses examples for concept learning. We describe the local focused property that functions must have for such a strategy to work. Finally, we develop an example selection heuristic, motivated by ϵ-focusing for training a computer vision system to perform a human Mace detection task.