对于相关性矩阵的双图
1Department of Statistics and Operations Research, Universitat Politècnica de Catalunya; Department of Biostatistics, University of Washington.
概括
本研究引入了一种新的代算法来调整相关性矩阵,比标准方法提高可视化准确性. 相关性计数棒提高了这些改进的相关性双图的解释性.
科学领域:
- 统计 统计 统计 统计
- 数据可视化 数据可视化
背景情况:
- 在双图中对相关矩阵的古典中心化方法是次优的.
- 基于主要组件分析 (PCA) 的相关性双图有局限性.
- 最近的进展包括对相关联双图的单个标量调整.
研究的目的:
- 介绍一种代算法,用于对应矩阵的列调整.
- 与单个标量调整相比,提高适合性.
- 评估拟议方法的实际实用性,并提高可视化解释性.
主要方法:
- 使用加权交替最小平方算法进行灵活的标量调整.
- 开发一个代算法,用于特定列的标量调整.
- 使用相关性计数棒有助于双图解释性.
主要成果:
- 建议的代列调整比单个标量调整提高了适合性.
- 新的双图最初的解释性较差,但通过相关联计数棒变得更加清晰.
- 权重根平均平方误差 (RMSE) 证实了改进的低维近似值.
结论:
- 代列调整提供了卓越的相关性矩阵近似.
- 相关性计数棒是解释复杂的相关性双图的有效工具.
- 该方法为相关性矩阵可视化和分析提供了宝贵的进步.
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