动态模糊二叉决策树构造方法

A Method of Contruction for Dynamic Fuzzy Binary Decision Tree

动态模糊数据分析是海量数据处理的核心课题之一.讨论了动态模糊决策树的属性算法,通过动态模糊二叉决策树的介绍,给出了动态模糊决策树中各结点以及各层对实例集划分之间的关系.由于划分格是对论域的划分,进一步定义了动态模糊划分格,给出了关于动态模糊决策树各层对实例集划分组成的集合的定理,并且证明了动态模糊决策树的各层对实例集的划分组成的集合既是一个线性有序集也是一个动态模糊划分格等.

The dynamic fuzzy data analysis is one of the key topics for mass data. Now many researchers use fuzzy logic for analysis. This article discusses the properties algorithm of dynamic fuzzy decision tree. It gives the dynamic fuzzy binary decision tree and the relation between the nodes and the layers of the set of instances. The partition lattice is for the domain of discourse. It defines the dynamic fuzzy partition Lattice, and gives the theorems of Layers for the set of instances on the dynamic fuzzy decision tree. It proves that the set is a linearly ordered and that it is also dynamic fuzzy partition lattice.