High-Dimensional Data Classification in Concentric Coordinates
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1866915408318038016 |
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| author | Williams, Alice Kovalerchuk, Boris |
| author_facet | Williams, Alice Kovalerchuk, Boris |
| contents | The visualization of multi-dimensional data with interpretable methods remains limited by capabilities for both high-dimensional lossless visualizations that do not suffer from occlusion and that are computationally capable by parameterized visualization. This paper proposes a low to high dimensional data supporting framework using lossless Concentric Coordinates that are a more compact generalization of Parallel Coordinates along with former Circular Coordinates. These are forms of the General Line Coordinate visualizations that can directly support machine learning algorithm visualization and facilitate human interaction. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_18450 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | High-Dimensional Data Classification in Concentric Coordinates Williams, Alice Kovalerchuk, Boris Human-Computer Interaction Machine Learning The visualization of multi-dimensional data with interpretable methods remains limited by capabilities for both high-dimensional lossless visualizations that do not suffer from occlusion and that are computationally capable by parameterized visualization. This paper proposes a low to high dimensional data supporting framework using lossless Concentric Coordinates that are a more compact generalization of Parallel Coordinates along with former Circular Coordinates. These are forms of the General Line Coordinate visualizations that can directly support machine learning algorithm visualization and facilitate human interaction. |
| title | High-Dimensional Data Classification in Concentric Coordinates |
| topic | Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2507.18450 |