中文摘要：

提出一种基于Madaline网络敏感性的主动学习算法。首先用部分样本训练Madaline网络，然后以Madaline网络输出对其输入在给定样本点附近变化的敏感性为尺度，主动从未参与训练的样本中挑选敏感性相对大的样本继续进行训练，循环反复这个过程直到满足训练要求为止。实验验证了该主动学习算法处理离散分类问题的有效性和可行性。

英文摘要：

This paper presents an active learning algorithm based on the Madaline network＇s output sensitivity due to its input variation near a given sample. First, a portion of samples are used to train a Madaline network. Then, based on the sensitivity of the network, some other samples with higher sensitivity are actively selected and added into the training data to continue the training of the network. This process is repeated until the training requirement is met. Experiments verified the effectiveness and feasibility of the proposed active learning algorithm in treating discrete classification problems.