Algorithm Comparative Analysis with Stepwise Line arR ge ression and N eural Ne twork
TAN Li-yun
LIU Hai-sheng
TAN Long
Abstract：Gradient linear regression can well solve the occurrence of Multicollinearity , so the gradient regres-sion analysis is analytical method to research the correlation among multivariable.Intelligent algorithm is one of the dominant methods in modern data analysis.Both of the methods above are applied to one example and further to be compared.The forecasted result shows:for the accuracy of the forecasted results , when the num-ber of hidden layer is consistent ,RBF radial basis neural networks >BP neural networks >Gradient linear regression >ELM limit machine learning.Through the analysis of comparison , we infer that the accuracy and error of neural networks is smaller than the regression model.
Keywords：stepwise linear regressionBP neural networkRBF neural networkELM Extreme Learning Ma-chine
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 60-65 )