关键词: 粗糙集, 正域, 手写识别, 特性选择, 监督学习

Abstract: According to the characteristics of handwritten letter recognition, a new handwritten letter recognition algorithm is proposed based on the rough set theory. The hypothesis of normal distribution has been tested to ensure the reliability of the collected samples. By using upper approximation, lower approximation, as well as positive region of rough set, feature selection is made in order to simplify the decision-making system. Classification rules are then extracted from the simplified decision-making system. Experimental results show that the new algorithm has higher recognition accuracy, and is feasible and effective.

Key words: rough set, positive region, handwriting recognition, feature selection, supervised learning