摘要
为了对大数据分析处理方式进行优化改进,研究在增量学习算法的基础上构建径向基函数大数据处理模型,加入定长滑动窗口进行改进优化,实现窗口式的在线学习数据处理;对动态流式大数据进行高效处理,提升处理模型的运行效率和性能。实验表明该模型在电子商务领域大数据处理中的应用效果良好,预测精准度较高。
In order to optimize and improve the big data analysis and processing method,the radial basis function big data processing model is constructed based on the incremental learning algorithm,and the fixed length sliding window is added for improvement and optimization,so as to realize the window online learning data processing to process the dynamic streaming big data efficiently,which could improve the operational efficiency and performance of the processing model.The experiment show that this model has a good application effect in big data processing in E-commerce field,and has high prediction accuracy.
作者
吕波
LV Bo(School of Ya’an Polytechnic College,Ya’an 625000,Sichuan Province,China)
出处
《信息技术》
2023年第3期45-50,56,共7页
Information Technology
基金
雅安职业技术学院5G技术应用中心(YZYJG201907)。
关键词
大数据
增量学习算法
径向基函数
在线学习
电子商务
big data
incremental learning algorithm
radial basis function
online learning
E-commerce
