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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2509.15143 |
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| _version_ | 1866912592854777856 |
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| author | Lee, Jaeho Kim, Kangjin Lee, Gyeong Taek |
| author_facet | Lee, Jaeho Kim, Kangjin Lee, Gyeong Taek |
| contents | This paper proposes the Next-Depth Lookahead Tree (NDLT), a single-tree model designed to improve performance by evaluating node splits not only at the node being optimized but also by evaluating the quality of the next depth level. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_15143 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Next-Depth Lookahead Tree Lee, Jaeho Kim, Kangjin Lee, Gyeong Taek Machine Learning This paper proposes the Next-Depth Lookahead Tree (NDLT), a single-tree model designed to improve performance by evaluating node splits not only at the node being optimized but also by evaluating the quality of the next depth level. |
| title | Next-Depth Lookahead Tree |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2509.15143 |