This paper introduces an innovative method for traversing binary decision trees using arithmetic operations. We present a suite of binary tree traversal algorithms that leverage novel representation matrices to flatten the full binary tree structure and embed the aggregated internal node decisions into a single vector. Our approach, grounded in maximum inner product search, offers new insights into decision tree partitioning.

翻译：本文提出了一种利用算术运算遍历二叉决策树的创新方法。我们开发了一套二叉树遍历算法，这些算法通过新颖的表示矩阵将完全二叉树结构扁平化，并将聚合的内部节点决策嵌入到单个向量中。我们的方法基于最大内积搜索，为决策树划分提供了新的见解。