在三维空间中使用平面和切片进行鲁棒双色分类
Robust Bichromatic Classification in 3D Using Planes and Slices
首次发表
浏览论文内容
中文总结 AI 辅助
研究三维空间中两组点的分离问题，基于线性约束分类器确保对异常值鲁棒，沿用前人方法，利用点与平面对偶性针对多种分类器及异常值定义提出算法。
中文摘要 AI 辅助
给定三维空间\(R\)和\(B\)中的两组点，我们希望使用基于线性约束的分类器分离这两组点，同时确保对异常值具有鲁棒性。Glazenburg等人在二维空间中研究过该问题。我们沿用他们的方法，针对多种异常值定义下的多种分类器提出了各种算法。我们的算法主要依赖于三维空间中点与平面的对偶性。
英文摘要
Given two sets of points in 3-dimensional space $R$ and $B$, we want to separate these two sets of points using a classifier based on linear constraints, while ensuring robustness against outliers. The problem was studied in $\mathbb{R}^2$ by Glazenburg et al. We follow their approach and present various algorithms for many types of classifiers under various definitions of outliers. Our algorithms rely mainly on the duality of points and planes in $\mathbb{R}^3$.
