摘要
有序分类是现实生活中广泛存在的一种分类问题。基于排序熵的有序决策树算法是处理有序分类问题的重要方法之一,这种方法是以排序互信息作为启发式来构建有序决策树。基于这项工作,通过引入模糊有序熵,并以模糊有序互信息作为启发式构建模糊有序决策树,对有序决策树进行了扩展。这两种算法在实际应用中各有自己的优劣之处,从四个方面对这两种算法进行了详细的比较,并指出了这两种算法的异同及优缺点。
Ordinal classification tasks widely exist in real life. Rank entropy based ordinal decision tree is one of the most important ways of dealing with ordinal classification problems. This decision tree algorithm selects rank mutual information as a heuristic. This paper introduces fuzzy rank entropy to construct an algorithm for building a fuzzy ordinal decision tree, which is an extension of ordinal decision tree. Both of them have been applied to dispose the ordinal classification tasks in a wide range. This paper compares the two algorithms based on four aspects, and shows their comparative advantages and disadvantages.
出处
《计算机科学与探索》
CSCD
2013年第11期1018-1025,共8页
Journal of Frontiers of Computer Science and Technology
基金
国家自然科学基金
河北省自然科学基金
河北大学自然科学基金
河北大学教育教学改革研究项目~~
关键词
有序分类
模糊有序互信息
有序决策树
ordinal classification
fuzzy rank mutual information
ordinal decision tree
