用二维图谱可视化分类器性能,一键对比各类场景下的表现。
A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers
- 用Tile图谱将无穷多排序指标映射到二维空间,统一展示性能
- 通过74个分割模型实测,揭示不同场景下最优模型差异
- 为分析者、设计者等四类用户定制解读视角,实用性强
准确理解分类器性能在多种场景中至关重要。然而,现有文献常仅依赖一两个标准评分来比较分类器,难以捕捉特定应用的需求细节。近期提出的Tile是一种可视化工具,可将无穷多的排序指标组织成二维地图。借助Tile,能够高效比较分类器,展现所有可能的应用偏好,而无需依赖一对评分。本文以四位典型用户(理论分析者、方法设计者、基准测试者、应用开发者)为例,介绍适配其需求的多种解释性呈现方式,并通过四个场景对74个前沿语义分割模型进行排名与分析。结果表明,Tile能在单一可视化中有效捕捉分类器行为,同时兼容无限多的排序指标。配套代码已提供于补充材料。
原文摘要 · Abstract (English)
Properly understanding the performances of classifiers is essential in various scenarios. However, the literature often relies only on one or two standard scores to compare classifiers, which fails to capture the nuances of application-specific requirements. The Tile is a recently introduced visualization tool organizing an infinity of ranking scores into a 2D map. Thanks to the Tile, it is now possible to compare classifiers efficiently, displaying all possible application-specific preferences instead of having to rely on a pair of scores. This hitchhiker's guide to understanding the performances of two-class classifiers presents four scenarios showcasing different user profiles: a theoretical analyst, a method designer, a benchmarker, and an application developer. We introduce several interpretative flavors adapted to the user's needs by mapping different values on the Tile. We illustrate this guide by ranking and analyzing the performances of 74 state-of-the-art semantic segmentation models through the perspective of the four scenarios. Through these user profiles, we demonstrate that the Tile effectively captures the behavior of classifiers in a single visualization, while accommodating an infinite number of ranking scores. Code for mapping the different Tile flavors is available in supplementary material.
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