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The Modeling and Simulation of Data Clustering Algorithms in Data Mining with Big Data

机译:数据集群Alg的建模与仿真截止期与大数据的数据挖掘

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摘要

Big Data is a popular cutting-edge technology nowadays. Techniques and algorithms are expanding in different areas including engineering, biomedical, and business. Due to the high-volume and complexity of Big Data, it is necessary to conduct data pre-processing methods when data mining. The pre-processing methods include data cleaning, data integration, data reduction, and data transformation. Data clustering is the most important step of data reduction. With data clustering, mining on the reduced data set should be more efficient yet produce quality analytical results. This paper presents the different data clustering methods and related algorithms for data mining with Big Data. Data clustering can increase the efficiency and accuracy of data mining.
机译:大数据是一个受欢迎的尖端技术如今。在不同的领域,包括工程、生物医学和业务。大数据的复杂性,有必要当数据进行数据预处理方法挖掘。清洁、数据集成、数据简化和数据转换。减少数据的重要一步。聚类,挖掘数据集应该减少更高效的农产品质量分析结果。聚类方法和相关算法数据挖掘大数据。增加数据的效率和准确性挖掘。

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