A novel Supervised Competitive Learning algorithm

作者：Dai, Qun^*; Song, Gang

来源：Neurocomputing, 2016, 191: 356-362.

DOI：10.1016/j.neucom.2016.01.045

• Competitive learning
• Supervised Competitive Learning (SCL) algorithm
• Multiple Classifier Systems (MCSs)
• Ordinary Supervised Learning (OSL) algorithm
• Pattern classification

Competitive learning is a mechanism well-suited for the learning paradigm of regularity detection, and is typically an unsupervised learning mechanism. However, in this work, a novel Supervised Competitive Learning (SCL) algorithm is proposed for the generation of Multiple Classifier Systems (MCSs), which is substantially supervised. SCL algorithm seeks to strengthen simultaneously both the accuracy of and the diversity among the base classifiers in the MCSs, in a supervised and competitive manner. Our inspiration for the development of SCL algorithm comes from the modern education concept and those classical competitive learning algorithms intuitively. It is found through the experimental study of this work that, SCL algorithm effectively improves the classification and generalization performance of the constructed MCSs.

• 出版日期2016-5-26
• 单位南京航空航天大学