Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914839945805824 |
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| author | Heiter, Edith Martens, Liesbet Seurinck, Ruth Guilliams, Martin De Bie, Tijl Saeys, Yvan Lijffijt, Jefrey |
| author_facet | Heiter, Edith Martens, Liesbet Seurinck, Ruth Guilliams, Martin De Bie, Tijl Saeys, Yvan Lijffijt, Jefrey |
| contents | This paper presents TRACE, a tool to analyze the quality of 2D embeddings generated through dimensionality reduction techniques. Dimensionality reduction methods often prioritize preserving either local neighborhoods or global distances, but insights from visual structures can be misleading if the objective has not been achieved uniformly. TRACE addresses this challenge by providing a scalable and extensible pipeline for computing both local and global quality measures. The interactive browser-based interface allows users to explore various embeddings while visually assessing the pointwise embedding quality. The interface also facilitates in-depth analysis by highlighting high-dimensional nearest neighbors for any group of points and displaying high-dimensional distances between points. TRACE enables analysts to make informed decisions regarding the most suitable dimensionality reduction method for their specific use case, by showing the degree and location where structure is preserved in the reduced space. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_12953 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE Heiter, Edith Martens, Liesbet Seurinck, Ruth Guilliams, Martin De Bie, Tijl Saeys, Yvan Lijffijt, Jefrey Graphics Human-Computer Interaction Machine Learning This paper presents TRACE, a tool to analyze the quality of 2D embeddings generated through dimensionality reduction techniques. Dimensionality reduction methods often prioritize preserving either local neighborhoods or global distances, but insights from visual structures can be misleading if the objective has not been achieved uniformly. TRACE addresses this challenge by providing a scalable and extensible pipeline for computing both local and global quality measures. The interactive browser-based interface allows users to explore various embeddings while visually assessing the pointwise embedding quality. The interface also facilitates in-depth analysis by highlighting high-dimensional nearest neighbors for any group of points and displaying high-dimensional distances between points. TRACE enables analysts to make informed decisions regarding the most suitable dimensionality reduction method for their specific use case, by showing the degree and location where structure is preserved in the reduced space. |
| title | Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE |
| topic | Graphics Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2406.12953 |