MCAL hybridizes particle swarm optimization(PSO)and cost-sensitive active learning(CAL)to improve the classification accuracy with multi-oracles and reduce the cost of labeling instances sampled.

为了提高分类精度和减少标注代价，该方法结合粒子群优化和代价敏感主动学习。