Research And Implementation Of Visual Example Teaching System For Ten Classical Big Data Algorithms

With the continuous deepening of big data applications,colleges and universities across the country have widely opened majors in data science and big data technology or big data management and application.In order to meet the urgent requirements of college teachers to describe big data algorithms in big data-related courses,this article will Research on algorithm principles and visualization of the ten classic algorithms in the big data field selected by the International Authoritative Academic Organization(ICDM)in December 2006,and implement a complete algorithm visualization example teaching system.The teaching system covers ten algorithms of C4.5,K-Means,KNN,SVM,EM,Apriori,CART,Page Rank,Ada Boost,and Naive Bayes.Each algorithm learning module includes algorithm introduction,data loading,algorithm processing process,and result visualization There are five aspects of display and algorithm help.At the same time,the system provides two functions: teacher setting management and student browsing and learning.The system is developed in Java language and runs in the B/S mode.The front and back ends are separated through the Spring Boot+Vue technology framework.The interface design uses the Vue-based component library Element UI to provide various styles,and is implemented through the Echarts open source visualization library Visual display of algorithm results.In addition,the system also uses JWT components to provide Token-based authentication capabilities to provide higher system security.The teaching system researched,designed and implemented in this paper brings together the implementation process of ten algorithms and a variety of visual display methods in a Web application.The idea of algorithm teaching with example data can also make students have a clearer and more thorough understanding of the algorithm.The teaching of big data algorithms by college teachers provides a convenient and efficient tool.