Arithmetical Binary Decision Tree Traversals

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autore principale: Zhang, Jinxiong
Natura: Preprint
Pubblicazione: 2022
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866909390077952000
author Zhang, Jinxiong
author_facet Zhang, Jinxiong
contents This paper introduces a series of methods 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 Boolean tests into a single binary vector. Our approach, grounded in maximum inner product search, offers new insights into decision tree.
format Preprint
id arxiv_https___arxiv_org_abs_2209_04825
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Arithmetical Binary Decision Tree Traversals
Zhang, Jinxiong
Machine Learning
Data Structures and Algorithms
Numerical Analysis
This paper introduces a series of methods 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 Boolean tests into a single binary vector. Our approach, grounded in maximum inner product search, offers new insights into decision tree.
title Arithmetical Binary Decision Tree Traversals
topic Machine Learning
Data Structures and Algorithms
Numerical Analysis
url https://arxiv.org/abs/2209.04825