Comparative Analysis Of Data Mining Using The Rought Set Method With K-Means Method

M. Nasution, Deci Irmayani, Ronal Watrianthos, S. Suryadi, Ibnu Rasyid Munthe
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引用次数: 3

Abstract

The purpose of this article is to compare between two data mining methods. Namely rought sets and k-means which both types of data aremining for clustering. Data mining itself is a method used to explore knowledge from a pile of data which so far has only been archived. While theclustering method itself is one method used to classify tendency, either the rought set method or k-means itself is used to find tendency or classify data.Both the method of rought set and k-means have the advantages of each according to needs. It is important to know what the advantages of eachmethod are before deciding to use which method to use
基于粗糙集方法和k -均值方法的数据挖掘比较分析
本文的目的是比较两种数据挖掘方法。即粗糙集和k-means这两种类型的数据都是用来聚类的。数据挖掘本身是一种用于从迄今为止仅存档的一堆数据中探索知识的方法。而聚类方法本身是一种用于趋势分类的方法,要么使用粗糙集方法,要么使用k-means本身来寻找趋势或分类数据。根据需要,粗糙集法和k-均值法各有优点。在决定使用哪种方法之前,了解每种方法的优点是很重要的
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