Design of a Multi-dimensional Similarity Big Data Classification System Based on SVM
Due to the similarity of big data itself,the classification accuracy of traditional data classification methods is low.Therefore,a design study on the multi-dimensional similarity big data classification system based on Support Vector Machine(SVM)is proposed.The MYC-JX8MMA7 core board as the development carrier of system design,build support vector machine linear regression model,by building a regression plane,and ensure all the multidimensional similar distance between big data and plane are in the minimum state,using the similarity of classification data and the best classification interface,between the data classification.In the test results,the classification result F1 Score was stable above 0.82,which was significantly better than the control group.
Support Vector Machine(SVM)multi-dimensional similarity big dataclassification systemMYC-JX8MMA7 core board
万方数据
维普
