| Presentation | 2022-06-27 Additive Cumulative Link Model with Total Variation Regularization Hiroya Iyori, Shin Matsushima, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In many fields such as medical research and social science, data on an ordinal scale are often obtained. Problems in which the target variable is given on the ordinal scale are called ordinal regression. Ordinal regression has different characteristics from those of regression and classification problems. In supervised learning of the ordinal regression problems, interpretability of the learned model is very important as well as its predictive performance. In this paper, we extend the generalized additive model with total variation regularization to ordinal regression problems and propose a additive cumulative logit model with total varition regularization (TVACLM) that achieves good performance in both perspectives from interpretability and prediction. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Ordinal regression / interpretability / additive model / total variation regularization |
| Paper # | NC2022-8,IBISML2022-8 |
| Date of Issue | 2022-06-20 (NC, IBISML) |
| Conference Information | |
| Committee | NC / IBISML / IPSJ-BIO / IPSJ-MPS |
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| Conference Date | 2022/6/27(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hiroshi Yamakawa(Univ of Tokyo) / Masashi Sugiyama(Univ. of Tokyo) |
| Vice Chair | Hirokazu Tanaka(Tokyo City Univ.) / Toshihiro Kamishima(AIST) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Hirokazu Tanaka(NTT) / Toshihiro Kamishima(NICT) / Koji Tsuda(NTT) / (Hokkaido Univ.) |
| Assistant | Yoshimasa Tawatsuji(Waseda Univ.) / Tomoki Kurikawa(KMU) / Yoshinobu Kawahara(Osaka Univ.) / Taiji Suzuki(Tokyo Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / Special Interest Group on Bioinformatics and Genomics / Special Interest Group on Mathematical Modeling and Problem Solving |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Additive Cumulative Link Model with Total Variation Regularization |
| Sub Title (in English) | |
| Keyword(1) | Ordinal regression |
| Keyword(2) | interpretability |
| Keyword(3) | additive model |
| Keyword(4) | total variation regularization |
| 1st Author's Name | Hiroya Iyori |
| 1st Author's Affiliation | the University of Tokyo(Univ. of Tokyo) |
| 2nd Author's Name | Shin Matsushima |
| 2nd Author's Affiliation | the University of Tokyo(Univ. of Tokyo) |
| Date | 2022-06-27 |
| Paper # | NC2022-8,IBISML2022-8 |
| Volume (vol) | vol.122 |
| Number (no) | NC-89,IBISML-90 |
| Page | pp.pp.69-75(NC), pp.69-75(IBISML), |
| #Pages | 7 |
| Date of Issue | 2022-06-20 (NC, IBISML) |