摘要
通过对基金数据的抽象,建立了基于数据量类型的数据挖掘模型,采用传统Apriori算法的设计思想,设计了基于数据量的支持度计算公式,改进了传统Apriori算法以适应新的支持度,从而提高了规则的准确性,可为基金经理和投资人提供决策依据。
Data model applying for data-density mining is set up through the Abstraction of fund data.Traditional apriori algorithm is used in its design.The support calculation formula is based on the amount of data.The traditional apriori algorithm is improved for the new support.Thereby it increases the accuracy of the rules and provides a basis of decision-making for fund managers and investors.
出处
《桂林理工大学学报》
CAS
北大核心
2010年第3期449-451,共3页
Journal of Guilin University of Technology
基金
辽宁省教育厅科研项目(2008314)
关键词
关联规则
基金
数据挖掘
数据量
association rules
fund
data mining
data-density
