| Presentation | 2004/9/4 Regression Trees and Its Application to Classification Problems Toshikazu Wada, Takayuki Nakamura, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper presents evolutional history of regression trees, a novel regression tree called PaLM-tree, and its application to Computer Vision and Pattern Recognition problems. Regression tree is a tree representation of nonlinear function, which is mainly investigated in the fields of Machine Learning and Data Mining. The original regression tree is a simple tree representation holding function values at leaves (terminated nodes). Linear regression tree extends the function values to linear regression coefficients. Since these regression trees are designed for rule-extraction, most of them are single valued for representing nonlinear scalar functions. PaLM-tree is a multi-valued extension of the linear regression tree with Split-and-Merge tree construction. PaLM-tree can be applied to varieties of nonlinear mapping learning problems. This paper also presents applications of PaLM-tree involving image segmentation, camera calibration and imitating classifiers. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | PRMU2004-80 |
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| Committee | PRMU |
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| Conference Date | 2004/9/4(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Pattern Recognition and Media Understanding (PRMU) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Regression Trees and Its Application to Classification Problems |
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| 1st Author's Name | Toshikazu Wada |
| 1st Author's Affiliation | Department of Computer and Communication Sciences Faculty of Systems Engineering, Wakayama University() |
| 2nd Author's Name | Takayuki Nakamura |
| 2nd Author's Affiliation | Department of Computer and Communication Sciences Faculty of Systems Engineering, Wakayama University |
| Date | 2004/9/4 |
| Paper # | PRMU2004-80 |
| Volume (vol) | vol.104 |
| Number (no) | 291 |
| Page | pp.pp.- |
| #Pages | 8 |
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