The recent advancements in machine learning have motivated researchers to generate classification models dealing with hundreds of classes such as in the case of image datasets. However, visualization of classification models with high number of classes and inter-model comparison in such classification problems are two areas that have not received much attention in the literature, despite the ever-increasing use of classification models to address problems with very large class categories. In this paper, we present our interactive visual analytics tool, called Circles, that allows a visual inter-model comparison of numerous classification models with 1K classes in one view. To mitigate the tricky issue of visual clutter, we chose concentric a radial line layout for our inter-model comparison task. Our prototype shows the results of 9 models with 1K classes

翻译：机器学习的最新进展促使研究者生成处理数百类别（如图像数据集）的分类模型。然而，尽管分类模型在解决具有极多类别的任务中应用日益广泛，但高类别分类模型的可视化以及此类分类问题中的模型间比较，在文献中尚未得到充分关注。本文提出名为Circles的交互式可视化分析工具，该工具可在单一视图中对多达1000个类别的多个分类模型进行可视化模型间比较。为解决视觉杂乱这一棘手问题，我们针对模型间比较任务选择了同心径向线布局。我们的原型展示了9个包含1000个类别的模型的结果。