基于大数据的预测处理模式研究
首发时间:2016-12-16
摘要:随着大数据时代的来临,人类社会已经进入一个崭新的数字时代。大数据的时代里 ,数据的产生和收集是基础,数据挖掘是关键,在日新月异的应用背后,产生的是数据的爆炸式增长和来自于大数据分析的挑战,如何有效的利用这些数据成为一个难题。对超大规模数据进行高效分析、利用已知数据进行大数据各种预测的模型的研究就尤为重要,其中,关键问题是对超大规模数据进行高效分析、利用已知数据进行大数据各种预测的模式是什么?本文结合大数据时代的数据特点,研究大数据的预测处理模式,提出一种算法融合的模型框架,并通过实验数据集验证模式,得到优选的大数据预测处理模式。
关键词: 大数据 数据挖掘 特征工程 模型融合 Hadoop
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Study on Prediction Processing Model Based on Large Data
Abstract:With the advent of the era of big data, human society has entered a new digital era. In the era of big data, the generation and collection of data is based on data mining is the key, behind the ever-changing application, explosive data growth to challenge big data analysis, how to effectively use these data is also a problem. It is very important to analyze the large-scale data efficiently and make use of the known data to carry on the research of the large data forecasting. The key problem is to analyze the super-large-scale data efficiently and use the known data to forecast the large data. What is it? In this paper, the characteristics of the data era of big data, the researchers predict large data processing mode, the model framework proposed an algorithm fusion and experimental data sets verify mode, a preferred Big Data predictive processing mode.
Keywords: Big Data Data Mining Feature Engineering Model Fusion Hadoop
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