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.
这样神经网络可应用于模式识别的特征提取、聚类分析、边缘检测、信号增强以及噪声抑制、数据压缩等各个环节。
This neural network pattern recognition can be applied to feature extraction, clustering analysis, edge detection, signal enhancement and noise suppression, data compression, such as various links.
线性判别分析是一种较为普遍的用于特征提取的线性分类方法。
Analysis is one of the most popular linear classification techniques for feature extraction.
应用推荐