一种递增式归纳学习算法  

Incremental Learning Algorithm of Induction

作　　者：程玉胜[1] 张春梅[1] 胡学钢[2] 

机构地区：[1]安庆师范学院数学计算机系,安徽安庆246011 [2]合肥工业大学计算机学院,安徽合肥230009

出　　处：《重庆大学学报（自然科学版）》2004年第4期44-48,共5页Journal of Chongqing University

基　　金：国家自然科学基金课题资助项目(69985004);安徽省教育厅自然科学研究项目(2004kj264)

摘　　要：笔者提出的递增式决策函数生成算法是在改造后的分辨矩阵下完成的,更有利于编程实现;避免了传统粗集方法对数据作一次性处理生成庞大的决策矩阵,从而有效解决了在处理大规模数据库时内存不足问题;由于决策函数是递增式生成的,因此该算法适应了目前数据变化的特点,实现了新例的动态学习,因此这种对信息的重用,减少了数据挖掘的时间;同时,递增式决策函数生成算法从根本上解决了多类决策的递增式学习问题。The algorithm about incremental generating decision function is built by modifying the definition of discernibility matrixes. So it is programmed effectively in the computer. The discernibility matrixes is not generated because the great quantity of data is fetched one after another. The lack of memory is solved by handing data in large database. The algorithm is adapted to the dynamic data and is able to deal with dynamic learning. The time of Data Ming decreases because of information reuse. At the same time, the question of learning about multi-classes is solved in essence by using the incremental generating decision function.

关 键 词：机器学习 粗集 分辨矩阵 决策函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]