论文标题
可视化大规模分类器的分类结构
Visualizing Classification Structure of Large-Scale Classifiers
论文作者
论文摘要
我们提出了一种根据预测分数计算大规模分类中类相似性的度量。在文献中，这种措施尚未正式提出。我们展示了如何可视化类相似性矩阵可以揭示层次结构和控制类别的关系。通过具有各种分类器的示例，我们演示了这种结构如何帮助分析分类行为并推断潜在的角病例。一个示例的源代码可在https://github.com/bilalsal/blocks上作为笔记本提供
We propose a measure to compute class similarity in large-scale classification based on prediction scores. Such measure has not been formally pro-posed in the literature. We show how visualizing the class similarity matrix can reveal hierarchical structures and relationships that govern the classes. Through examples with various classifiers, we demonstrate how such structures can help in analyzing the classification behavior and in inferring potential corner cases. The source code for one example is available as a notebook at https://github.com/bilalsal/blocks
