Regression forecast model of support vector machine based on principal component analysis
Lei Wang
Abstract
Lei Wang
Abstract
Based on principal component analysis method,dimensions of samples are reduced,multiple regression forecast model is established based on principal component,coefficient of regression model is confirmed by using support vector machine,finally the example showed this model has higher forecast precision.
OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Based on principal component analysis method,dimensions of samples are reduced,multiple regression forecast model is established based on principal component,coefficient of regression model is confirmed by using support vector machine,finally the example showed this model has higher forecast precision.
Key concepts: Principal component analysis, Principal component regression, Support vector machine, Regression analysis, Computer science, Component (thermodynamics), Regression, Functional principal component analysis