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Interactive Visualization and Exploration of High-Dimensiona...

Interactive Visualization and Exploration of High-Dimensional Data

交互式可视化与高维数据探索

作     者:Waddell, Adrian 

作者单位:University of Waterloo 

学位级别:master

导师姓名:Wayne Oldford

授予年度:2016年

主      题:Interactive Data Visualization High-dimensional Data Statistical Visualization 

摘      要:Visualizing data is an essential part of good statistical practice. Plots are useful for revealing structure in the data, checking model assumptions, detecting outliers and finding unanticipated patterns. Post-analysis visualization is commonly used to communicate the results of statistical analyses. The availability of good statistical visualization software is key in effectively performing data analysis and in exploring and developing new methods for data visualization. Compared to static visualization, interactive visualization adds natural and powerful ways to explore the data. With interactive visualization an analyst can dive into the data and quickly react to visual clues by, for example, re-focusing and creating interactive queries of the data. Further, linking visual attributes of the data points such as color and size allows the analyst to compare different visual representations of the data such as histograms and *** this thesis, we explore and develop new interactive data visualization and exploration tools for high-dimensional data. The original focus of our research was a software implementation of navigation graphs. Navigation graphs are navigational infrastructures for controlled exploration of high-dimensional data. As part of this thesis, we developed the first interactive implementation of these navigation graphs called RnavGraph. With RnavGraph we explored various features for enhancing the usability of navigation graphs. We concluded that a powerful interactive scatterplot display and methods to deal with large graphs were two areas that would add great value to the navigation graph *** s scatterplot display proved to be particularly useful for data analysis and we continued our research with the design and implementation of a general-purpose interactive visualization toolkit called loon. The core contributions of loon are as follows. loon implements a general design for interactive statistical graphic displays that

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