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首页> 外文期刊>IEEE transactions on visualization and computer graphics >DimLift: Interactive Hierarchical Data Exploration Through Dimensional Bundling
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DimLift: Interactive Hierarchical Data Exploration Through Dimensional Bundling

机译:DimLift: Interactive Hierarchical Data Exploration Through Dimensional Bundling

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摘要

The identification of interesting patterns and relationships is essential to exploratory data analysis. This becomes increasingly difficult in high dimensional datasets. While dimensionality reduction techniques can be utilized to reduce the analysis space, these may unintentionally bury key dimensions within a larger grouping and obfuscate meaningful patterns. With this work we introduce &italic&DimLift&/italic&, a novel visual analysis method for creating and interacting with &italic&dimensional bundles&/italic&. Generated through an iterative dimensionality reduction or user-driven approach, &italic&dimensional bundles&/italic& are expressive groups of dimensions that contribute similarly to the variance of a dataset. Interactive exploration and reconstruction methods via a layered parallel coordinates plot allow users to &italic&lift&/italic& interesting and subtle relationships to the surface, even in complex scenarios of missing and mixed data types. We exemplify the power of this technique in an expert case study on clinical cohort data alongside two additional case examples from nutrition and ecology.

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