基于海量数据关联效应测度算法的设计

Design in Correlation Algorithm of Effect Measure Based on Massive Data

海量数据挖掘算法研究是当前数据挖掘研究领域的热点问题。以网络终端海量数据分布处理及软硬件资源共享为基础,以两变量线性关联效应测度学习算法设计为例,设计出基于超海量数据各终端数据分布处理的学习算法,并运用实验数据验证了该学习算法的有效性。该学习算法设计为海量数据云计算提供了应用思路。

The study of massive data mining algorithm is the research hotspot. On the basis of network terminal hardware and software information distributed processing as well as hardware and software resource sharing, taking two variables and linear correlation effect measure learning algorithm design as an example, the authors put forward learning algorithm based on massive data and the terminal data distribution processing. Experiments show that the learning algorithm is effective, which provides thought for cloud comouting of massive data.