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A Brief Analysis of Data Mining Techniques

机译:数据挖掘技术浅析

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摘要

Today, we live in the age of information. And we all know, where there is information, there is data. And currently, the amount of information present is humongous. Worse, every day the amount of information present is increasing. As a direct consequence of that, there is an enormous amount of data that is being generated on a day to day basis and the majority of that data is generally noise data (meaningless data). The data that is useful to us is quite less and is hidden in between all the useless data. Finding the useful data is like finding a pin in the haystack. This is where Data Mining and its techniques come to play. The data mining is the process of searching and then segmenting the data by discovering useful and interesting patterns as well as descriptive and predictive models from large scale data [1]. The objective of this paper is to review, analyze and then have the application of the different techniques which are used in Data mining and the discovery of knowledge in databases.
机译:今天,我们生活在信息时代。众所周知,哪里有信息,哪里就有数据。目前,信息量是巨大的。更糟糕的是,每天提供的信息量都在增加。这样做的直接结果是,每天都会产生大量数据,并且这些数据中的大多数通常是噪声数据(无意义的数据)。对我们有用的数据要少得多,并且隐藏在所有无用的数据之间。查找有用的数据就像在大海捞针中查找大头针。这就是数据挖掘及其技术发挥作用的地方。数据挖掘是通过从大型数据中发现有用和有趣的模式以及描述性和预测性模型来搜索并细分数据的过程[1]。本文的目的是回顾,分析然后应用在数据挖掘和数据库知识发现中使用的不同技术。

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