| Presentation | 2022-07-22 Bayes Optimal Approximation Algorithm by Boosting-like Construction of Meta-Tree Sets in Classification on Decision Tree Model Ryota Maniwa, Naoki Ichijo, Koshi Shimada, Toshiyasu Matsushima, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Decision trees are used for classification and regression such as predicting the objective variable corresponding to the new explanatory variable. In this study, decision trees are regarded as a data generation model and we propose a prediction method based on Bayes decision theory. However, the computational complexity of calculating the prediction increases exponentially with the number of tree models, the depth of trees, and the dimensions of explanatory variables. There is a concept called ``meta-tree’’ which reduces the computational complexity in terms of the tree depth. Therefore, we also propose an efficient algorithm to predict the objective variable by creating multiple meta-trees sequentially. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Bayes Optimal Prediction / Decision Tree / Ensemble learning / Boosting / Meta-tree |
| Paper # | IT2022-28 |
| Date of Issue | 2022-07-14 (IT) |
| Conference Information | |
| Committee | IT |
|---|---|
| Conference Date | 2022/7/21(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okayama University of Science |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Freshman session, General |
| Chair | Tetsuya Kojima(Tokyo Kosen) |
| Vice Chair | Yasuyuki Nogami(Okayama Univ.) |
| Secretary | Yasuyuki Nogami(Saitamai Univ.) |
| Assistant | Takayuki Nozaki(Yamaguchi Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Information Theory |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Bayes Optimal Approximation Algorithm by Boosting-like Construction of Meta-Tree Sets in Classification on Decision Tree Model |
| Sub Title (in English) | |
| Keyword(1) | Bayes Optimal Prediction |
| Keyword(2) | Decision Tree |
| Keyword(3) | Ensemble learning |
| Keyword(4) | Boosting |
| Keyword(5) | Meta-tree |
| 1st Author's Name | Ryota Maniwa |
| 1st Author's Affiliation | Waseda University(Waseda Univ.) |
| 2nd Author's Name | Naoki Ichijo |
| 2nd Author's Affiliation | Waseda University(Waseda Univ.) |
| 3rd Author's Name | Koshi Shimada |
| 3rd Author's Affiliation | Waseda University(Waseda Univ.) |
| 4th Author's Name | Toshiyasu Matsushima |
| 4th Author's Affiliation | Waseda University(Waseda Univ.) |
| Date | 2022-07-22 |
| Paper # | IT2022-28 |
| Volume (vol) | vol.122 |
| Number (no) | IT-128 |
| Page | pp.pp.67-72(IT), |
| #Pages | 6 |
| Date of Issue | 2022-07-14 (IT) |