General Line Coordinates in 3D

• URL: http://arxiv.org/abs/2403.13014v1
• Date: Sun, 17 Mar 2024 17:42:20 GMT
• Title: General Line Coordinates in 3D
• Authors: Joshua Martinez, Boris Kovalerchuk,
• Abstract summary: Interpretable interactive visual pattern discovery in 3D visualization is a promising way to advance machine learning. It is conducted in 3D General Line Coordinates (GLC) visualization space, which preserves all n-D information in 3D.
• Score: 2.9465623430708905
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Interpretable interactive visual pattern discovery in lossless 3D visualization is a promising way to advance machine learning. It enables end users who are not data scientists to take control of the model development process as a self-service. It is conducted in 3D General Line Coordinates (GLC) visualization space, which preserves all n-D information in 3D. This paper presents a system which combines three types of GLC: Shifted Paired Coordinates (SPC), Shifted Tripled Coordinates (STC), and General Line Coordinates-Linear (GLC-L) for interactive visual pattern discovery. A transition from 2-D visualization to 3-D visualization allows for a more distinct visual pattern than in 2-D and it also allows for finding the best data viewing positions, which are not available in 2-D. It enables in-depth visual analysis of various class-specific data subsets comprehensible for end users in the original interpretable attributes. Controlling model overgeneralization by end users is an additional benefit of this approach.

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