Here is a compact representation of binary decision trees. We can explicitly draw the dependencies between prediction and binary tests in decision trees and construct a procedure to guide the input instance from the root to its exit leaf. And we provided a connection between decision trees and error-correcting output codes. Then we built a bridge from tree-based models to attention mechanisms.

翻译：本文提出了一种二元决策树的紧凑表示方法。我们能够显式地刻画决策树中预测结果与二元测试之间的依赖关系，并构建一个引导输入实例从根节点遍历至输出叶节点的过程。我们建立了决策树与纠错输出编码之间的理论联系，进而搭建了从树模型到注意力机制的桥梁。