Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (34): 1-4.

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Survey on active learning algorithms

LIU Kang, QIAN Xu, WANG Ziqiang   

  1. College of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing 100083, China
  • Online:2012-12-01 Published:2012-11-30


刘  康,钱  旭,王自强   

  1. 中国矿业大学(北京) 机电与信息工程学院,北京 100083

Abstract: As a method of constructing an effective training set, the goal of active learning algorithm is to find informative sample which can enhance the classification results of the model during the iteration, thereby reducing the size of the training set and improving the efficiency of the model within the limited time and resources. At present, active learning has become a hot issue in the field of pattern recognition, machine learning and data mining. The fundamental ideas, some latest research results and algorithm analysis of active learning are introduced. Some problems for further research are presented and analyzed.

Key words: active learning, pattern recognition, machine learning

摘要: 主动学习算法作为构造有效训练集的方法,其目标是通过迭代抽样,寻找有利于提升分类效果的样本,进而减少分类训练集的大小,在有限的时间和资源的前提下,提高分类算法的效率。主动学习已成为模式识别、机器学习和数据挖掘领域的研究热点问题。介绍了主动学习的基本思想,一些最新研究成果及其算法分析,并提出和分析了有待进一步研究的问题。

关键词: 主动学习, 模式识别, 机器学习