摘要
提出了多元数据的多点表示模型。该模型采用多个平面矢量来表示多元数据的各个属性变量。每个平面矢量用一个复变函数来描述,整个数据集表达为一个复变函数矩阵。该模型可以统一描述多种常用的图表示方法,如平行坐标、雷达图、星座图等。该表示模型的参数可以利用机器学习算法进行优化,从而有效地揭示数据结构并进行可视化模式识别。
The multiple points representation model is proposed in this paper. The attribute variables are represented by multiple plane vectors. Every plane vector is formulated by a complex function, and the dataset is expressed as a complex function matrix. Multiple graphical methods such as parallel coordinates, star glyph, constellation graph can be unified by this model. The repres- entation models' parameters can be optimized by machine learning algorithms so as to reveal the internal structure of original data and serve as a tool for visual pattern recognition.
出处
《燕山大学学报》
CAS
2008年第5期401-404,共4页
Journal of Yanshan University
基金
国家自然科学基金资助项目(60605006
60474065
60504035)
关键词
多点表示
矢量
复矩阵表示
参数优化
multiple points representation
vector
complex matrix representation
parameter optimization