Discussion on the Relation Between SVM Training Sample Size and Correct Forecast Ratio for Simulation Experiment Results

Shuguang Zhu,Fangzhou Zhu,Weibing Fan,Qian Mo,Zhiqiang Li,Xiaofeng Hu,Guangya Si

ICICTA), 2010 International Conference（2010）

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摘要

A series of support vector machine (SVM) forecast experiments are carried out to reveal the relation between the SVM training sample size and SVM correct forecast ratio for simulation experiment results. Experiment results show that the SVM correct forecast ratio increases to some extent with the number of training samples becoming more and then keeps unchanged even if the SVM training sample number increases further. And SVM has also been proved to be able to overcome the over-fitting issue always afflicting Back-Propagation Neural Networks (BPNN).

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over-fitting issue,training sample,svm training sample number,simulation experiment results,forecast ratio,simulation experiment,simulation experiment result,experiment result,svm training sample size,backpropagation,svm correct forecast ratio,correct forecast ratio,forecast experiment,backpropagation neural networks,support vector machine,training sample size,back-propagation neural networks,support vector machines,neural nets,intelligent networks,sample size,data models,testing,sampling methods,computer simulation,kernel,artificial neural networks,computer networks,technology forecasting,predictive models

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