一种基于PCA和系统成团法的聚类软件设计

提出一种基于主分量分析和系统成团法的快速聚类方法.通过构造主分量空间将分散在一组变量上的高维天体光谱投影到两个主分量上,每一个主分量都是原始变量的线性组合,主分量之间互为正交关系,在剔除冗余信息的同时,得到二维坐标;以此为输入,使用系统成团法进行聚类分析研究,实现高维天体光谱的快速自动分类处理.以上述方法为基础设计天体光谱自动分类软件,实现海量光谱的快速、准确分类.

Design of a PCA and Hierarchical Method Classification Software

An efficient and quick method based on 2-D pca and hierarchical clustering method is proposed. The coordinates are achieved by projecting the high dimensional celestial objects spectra data to the 2-D space after the principle component space is built, every principle component is the linear combination of the original variables and is irrelevant to each other. The coordinates can be clustered by hierarchical clustering method. An automatic celestial objects spectra classification software is designed based...