通过主成分分析法将众多指标进行综合，消除样本间的信息重叠，降低BP网络的输入维数。
Through principal component analysis, we have synthesized numerous indexes, (eliminated) information overlapping of the sample, and reduced the input dimension of BP network.
并对影响城市空气质量的5个主要因素进行主成分分析，找出最能代表原来数据信息的2至3个因子代替原来的5个变量。
Then 5 main factors affecting urban air quality to principal component analysis identify the most representative of the original data instead of the 2 to 3 factors 5 variables.
本文提出一种利用平行坐标图的多元信息表示对主成分分析特征提取方法进行优化的分类技术。
A novel method for optimizing the principle component analysis in feature extraction is proposed, which making use of parallel coordinate plot for graphical presentation of multivariate information.
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