基于粗糙集理论数据挖掘方法的网络聚类算法分析

Gathers the Network that the Theories Data Scoops out a Method to Gather a Type of Calculate Way Analysis According to the Coarseness

粗集理论作为智能信息处理技术的一个新成果,是由波兰科学家Z.Pawlak教授提出来的对不完整数据进行分析、推理、学习、发现的新方法。根据粗集理论的方法,数据挖掘就是给定知识表达系统的条件属性和结果(决策)属性,求出所有符合该知识的最小决策算法。网络数据挖掘的实施是从大量的、不完全的、有噪声的、模糊的、随机的数据中,提取隐含在其中,人们事先并不知道,但又是潜在有用的信息和知识的过程。该文基于粗糙集理论数据挖掘方法,对网络数据中的聚类算法进行了优化分析。

Thick gather theories is carry on analysis,reason logically,study to the not complete data,detection of new method.According to thick gather the method of the theories,the network data scoop out of implement from a great deal of of,imperfect of,misty of,withdraw in the random data implicit therein,people in advance and really don't know,but again is a latent and useful knowledge process.This text gathers the theories data to scoop out a method according to the coarseness,to the network data of gathered a type of calculate way to carry on excellent turn analysis.