基于云模型的连续属性整体离散化方法

An Global Discretization Algorithm for Continuous Attributes Based on Cloud Models

连续属性离散化是数据分析中重要的预处理过程,本文提出了一种基于云模型,融合相似云度量思想的连续属性整体离散化方法。它首先对例子集合在各个连续属性上的取值进行统一数量级别处理,选出分区基准属性,然后使用正态云模型对每个连续属性进行离散化.最后加以实验验证,指出该方法有一定的理论价值和实际意义.

Discretization of continuous features is an important process of data preprocessing. In this paper, a new method of discretization of continuous attributes based on cloud model and similar cloud is introduced, Inthe end , it is pointed out that the similar cloud and the measurement method has some theory value and real meanings..