Hyperdimensional Data Analysis Using Parallel Coordinates
Анализ многомерных данных с использованием параллельных координат
1990-09-01
SCID: 54.1/mf9bfu62
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axis permutationduality resultshigh-dimensional data analysisparallel coordinatesprojective transformation
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Abstract (AI)
This article presents the basic results of using the parallel coordinate representation as a high-dimensional data analysis tool. Several alternatives are reviewed. The basic algorithm for parallel coordinates is laid out and a discussion of its properties as a projective transformation is given. Several duality results are discussed along with their interpretations as data analysis tools. Permutations of the parallel coordinate axes are discussed, and some examples are given. Some extensions of the parallel coordinate idea are given. The article closes with a discussion of implementation and some of my experiences.
Key Findings
1
Extensions to the parallel coordinate concept and practical implementation experiences are provided.
2
Parallel coordinate representation is presented and validated as an effective tool for high-dimensional data analysis.
3
Permutations of parallel coordinate axes are examined, with examples showing their impact on data interpretation.
4
Several duality results for parallel coordinates are discussed and interpreted as useful data analysis tools.
5
The paper lays out the basic algorithm for parallel coordinates and analyzes its properties as a projective transformation.
Research Object
Parallel coordinate representation for high-dimensional data
Research Subject
Properties, algorithms, dualities, axis permutations, extensions and implementation aspects of using parallel coordinates as a tool for high-dimensional data analysis (i.e., its behavior as a projective transformation and related data-analysis interpretations)
Publication Details
Publication Date
1990-09-01
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