基于偏微积分分类数学模型的关联挖掘改进技术Association mining improved technology based on partial calculus classification mathematical model
温荣坤
摘要(Abstract)：
为了提高大数据环境下关联数据挖掘的效率和精度,提出基于分数偏微积分分类数学模型的关联挖掘方法。基于偏微积分原理塑造基于偏微积分方程的融合算法模型,实现大数据分类过程中的差异性数据融合;再通过偏微分分类数学模型的双边界收敛控制,在数据集合融入偏微积分分类数据模型,通过增减量支持向量完成数据的模糊控制,采用约束捆绑聚类算法对数据模型实施挖掘,获取子序列,在最小迭代次数和收敛下,通过测度信息调控,采用高斯核函数挖掘关联数据序列。实验结果说明,所提关联数据挖掘方法具有较高的挖掘效率和精度,稳定性强。
关键词(KeyWords)： 偏微积分分类;数学模型;关联挖掘;分数阶;收敛控制;挖掘效率
基金项目(Foundation): 云南省教育厅科学研究基金项目(2016ZDX273)~~
作者(Author): 温荣坤
DOI: 10.16652/j.issn.1004-373x.2018.13.022
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