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

最近机器学习的进展激发了研究人员生成处理百个类别（如图像数据集）的分类模型，但是在可视化高数量类别的分类模型和分类问题中模型间比较这两个领域尚未得到足够的关注。本文介绍了我们的交互式可视分析工具 Circles，允许在一视图中对数百个带有1K类别的分类模型进行模型间比较，为了缓解视觉杂乱问题，我们选择了同心径向线布局用于模型间比较任务。我们的原型展示了9个带有1K类别的模型结果。

Circles: 高类别数量多分类问题的模型间比较