A Comparative Analysis of Various Cluster Detection Techniques for Data Mining

Prashant Vats, Manju Mandot, A. Gosain
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引用次数: 4

Abstract

Data mining is a knowledge discovery technique, used for exploring the new facts and relationships among data. It enables a user to uncover hidden information among available datasets. Cluster detection is one of the major techniques, which is used for data mining. In the Cluster detection techniques, User performs mining of data by searching for cluster of elements that are similar to each other. Each implementation of the cluster detection techniques adopts a method of comparing the value of individual datasets with those in their centroids. So, in this paper we have enlisted a few of them. Based on certain parameters, we have carried out a comprehensive analysis of various clustering techniques.
数据挖掘中各种聚类检测技术的比较分析
数据挖掘是一种知识发现技术,用于探索数据之间新的事实和关系。它使用户能够发现可用数据集中的隐藏信息。聚类检测是用于数据挖掘的主要技术之一。在聚类检测技术中,User通过搜索彼此相似的元素簇来进行数据挖掘。每一种聚类检测技术的实现都采用一种将单个数据集的值与其质心中的值进行比较的方法。因此,在本文中,我们列出了其中的一些。基于一定的参数,我们对各种聚类技术进行了综合分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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