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首页> 外文期刊>International Journal of Computer Trends and Technology >Analysis of Data using K-Means Clustering Algorithm with Min Max Function
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Analysis of Data using K-Means Clustering Algorithm with Min Max Function

机译:使用具有最小最大函数的K均值聚类算法进行数据分析

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摘要

The information is currently used for wide range of applications. Data mining is a logical process that is used to search through large amount of data in order to find useful data. Data mining is studied for different databases. For the proper utilization of data the data analytics techniques are applied on the data. Data analytics uses clustering, normalization, etc. Clustering is the process of organizing the objects into groups whose members are similar in some way to others. Lot of work is done in this field by different researchers. In this work the new data analytics technique is proposed. The base technique is modified by the new proposed technique. New technique uses the min max function instead of the scaling. The new technique is proposed, designed, implemented in the R language. The results obtained and analysed. The new proposed technique gives the better and compact clusters.
机译:该信息当前被广泛应用。数据挖掘是一个逻辑过程,用于搜索大量数据以查找有用的数据。研究了针对不同数据库的数据挖掘。为了适当地利用数据,将数据分析技术应用于数据。数据分析使用聚类,规范化等。聚类是将对象组织为成员在某种程度上彼此相似的组的过程。不同领域的研究人员在该领域做了很多工作。在这项工作中,提出了一种新的数据分析技术。基本技术已通过新提出的技术进行了修改。新技术使用min max函数而不是缩放。以R语言提出,设计和实现了新技术。获得结果并进行分析。提出的新技术给出了更好,更紧凑的群集。

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