Arithmetical Binary Decision Tree Traversals
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2022
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866909390077952000 |
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| 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 |