Analytics of Specialized Data by Data Mining

S. Gnanamurthy, V. K. Kaliappan
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引用次数: 0

Abstract

In this paper, we are trying to discover Predictive Analytics by means of combining special information mining methods with large data. Predictive lookup consists of a number of mathematical and analytical techniques to increase new techniques for doable prediction possibilities. The paper also portrays the integration of Big Data characteristics as the foundation of Data Mining by Apache Hadoop's usefulness in achieving the above. With the resource of accessible statistics mining techniques, predictive analytics predicts the activities in future and can make tips referred to as prescriptive analytics. This evaluates paper offers clear thought to follow facts mining strategies and predictive analytics on distinctive clinical dataset to predict a variety of ailments with accuracy levels, execs and cons that conclude about the troubles of these algorithms and futuristic processes on huge data.
基于数据挖掘的专业数据分析
在本文中,我们试图通过将特殊的信息挖掘方法与大数据相结合来发现预测分析。预测查找由许多数学和分析技术组成,以增加可实现预测可能性的新技术。本文还描述了大数据特征的集成作为数据挖掘的基础,Apache Hadoop在实现上述目标方面的有用性。利用可访问的统计挖掘技术资源,预测分析可以预测未来的活动,并可以提出被称为规定性分析的提示。这篇评估论文提供了清晰的思路,以遵循事实挖掘策略和独特的临床数据集的预测分析,以准确水平预测各种疾病,高管和cons总结了这些算法和未来处理大数据的麻烦。
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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