【摘要】 文章深入分析了目前普遍采用的主成分分析——神经网络模型应用中存在的不合理问题,通过推导指出错误所在,提出了相应的改进方案.为了验证改进模型的有效性,以UCI机器学习库中的数据集为样本,选取有导师BP神经网络和无导师SOM神经网络,建立改进的主成分分析——神经网络模型,并与传统主成分分析——神经网络模型进行比较测试,实验结果表明改进的模型效果更优.更多还原

【Abstract】 This essay thorough analyze the principal component analysis which was widely used at present the application of Neural Networks is unreasonable.By inference,we know where the error is,and propose the reform program.In order to verify the validity of the improved model,we take UCI machine learning data as samples,and select the tutor BP Neural Network and the unsupervised SOM Neural Network to improve the principal component analysis the Neural Network model.Compared with the traditional principal component analysis and the Neural Network model,we can find that the improved model is better than the other.更多还原