A new multivariate data visualization method named point-score parallel coordinates (PSPC) is proposed in this paper.
提出了一种多元数据的点得分平行坐标表示及可视化分析方法。
A subspace graphical representation model of multivariate data is proposed, which unites several traditional multivariate data visualization methods into the same representation framework.
本文提出多元数据的子空间坐标图表示模型，该模型可以将这些传统多元图表示方法统一到同一个表示框架。
Pattern Recognition; Visualization; Multivariate Data; Graphical Representation; Geometric Algebra; Subspace Coordinates; Optimization.
模式识别；可视化；多元数据；图表示；几何代数；子空间坐标；优化。
Pattern Recognition; Visualization; Multivariate Data; Graphical Representation; Geometric Algebra; Subspace Coordinates; Optimization.
模式识别；可视化；多元数据；图表示；几何代数；子空间坐标；优化。
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