Development of Visual Programming Environment for Exploratory Data Analysis

探索性数据分析可视化编程环境的开发

• 批准号: 07558149
• 负责人: SATO Yoshiharu
• 金额: $ 3.07万
• 依托单位: HOKKAIDO UNIVRSITY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (A)
• 财政年份: 1995
• 资助国家: 日本
• 起止时间: 1995 至 1997
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07558149/
• 关键词: Statistical Package; Visual Data Analysis; Statistical Graphics; Neural Networks

In computer science, "Visualization" is one of the most attractive keywords. "Visualization" is useful not only to reveal data but to deal with analysis processes. Statisticians are often forced to apply many methods to the same data in their analysis since they wants to find the most reasonable result. A lot of results they made, however, may perplex them. If they can view an analysis flow (made of some statistical methods) on the graphical display, they can easily find the relations between data and applied methods. It is called "Visualization of Execution."As we described, "Visualization" has much power then we try to build "Visual Environment, " which synthesizes both "Visualization" merits. In short, our target is to build the system which can view, display data and construct analysis flows and execute them in the sameenvironment. In the system, if we can add and execute some statistical methods in an analysis flow, we can easily change some methods or apply another procedure to the original data or intermediate ones.We had already developed the prototypes and now improve it on the workstation with Tcl/Tk environment for its interoperability. In addition, this idea is also effective for novices in statistics but they have less knowledge on statistics then may make a meaningless statistical flow. We have already recognized this problem and tried to add a supporting module which makes use of technique on knowledge engineering.Especially, in the process of the research project, we have investigated the hard/software for the visual programming environment and have discussed the critical issues for the practical use of the environment

在计算机科学中，“可视化”是最吸引人的关键词之一。“可视化”不仅有助于揭示数据，而且有助于处理分析过程。统计学家在分析同一数据时，为了得到最合理的结果，常常不得不采用多种方法。然而，他们取得的许多成果可能会使他们感到困惑。如果他们可以在图形显示器上查看分析流程（由一些统计方法组成），他们可以轻松找到数据和应用方法之间的关系。它被称为“执行的可视化”。正如我们所描述的，“可视化”有很大的力量，然后我们试图建立“可视化环境”，它综合了“可视化”的优点。总之，我们的目标是建立一个系统，可以查看，显示数据和构造分析流程，并在同一环境中执行它们。在系统中，如果我们可以在一个分析流程中添加和执行一些统计方法，我们可以很容易地改变一些方法或应用另一个过程的原始数据或中间的。我们已经开发了原型，现在改进它的工作站与Tcl/Tk环境的互操作性。此外，这个想法也是有效的统计新手，但他们对统计知识较少，然后可能会使一个毫无意义的统计流。我们已经认识到这一问题，并尝试增加一个支持模块，利用知识工程的技术，特别是在研究项目的过程中，我们研究了可视化编程环境的硬件和软件，并讨论了环境实用化的关键问题

项目成果

M.Mizuta: "Bounded Algebraic Curve Fitting for Multidimensional Data Using the Least-Squares Distance" Data Science,Classification,and Related Methods,Springer. 228-237 (1995)

M.Mizuta：“使用最小二乘距离的多维数据的有界代数曲线拟合”数据科学、分类和相关方法，Springer。

M.Sato and Y.Sato: "On a General Fuzzy Additive Clustering Model" International Journal of Intelligent Automation and Soft Computing. 1(4). 439-448 (1995)

M.Sato 和 Y.Sato：“关于一般模糊加性聚类模型”国际智能自动化和软计算杂志。

A.Suzukawa and Y.Sato: "A Generalization of Testing Independence of Sets of Variates" Journal of Japan Statistical Society. 25(1). 71-80 (1995)

A.Suzukawa 和 Y.Sato：“变量集测试独立性的推广”日本统计学会杂志。

T.Murai, H.Kanemitsu, and M.Shimbo: "Fuzzy Sets and Binary-Proximity-Based Rough Sets." Information Sciences. 104(1/2). 49-80 (1998)

T.Murai、H.Kanemitsu 和 M.Shimbo：“模糊集和基于二元邻近性的粗糙集”。

M.Mizuta: "Bounded Algebraic Curve Fitting for Multidimensional Data Using the Least-Squares Distance" Data Science, Classification, and Related Methods Springer.610-616 (1998)

M.Mizuta：“使用最小二乘距离的多维数据的有界代数曲线拟合”数据科学、分类和相关方法 Springer.610-616 (1998)