| Presentation | 2012-11-08 An Ordinal Regression Model Based on Logistic Regression Models and Its Fast Sparse Bayesian Learning Kazuhisa NAGASHIMA, Masato INOUE, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The common solution to the ordinal regression problem uses the model in which noise-contained inputs are deterministically labeled according to domains partitioned by several thresholds. Its likelihood is given by the product of the differences of probit functions and this likelihood prevents common analytical approaches such as differentiation of the log likelihood. In this manuscript, we introduce a model in which noise-free inputs are probabilistically labeled. More specifically, this model is constructed by using logistic regression models. We found that this model is easy to analyze. We also show that its 'fast' sparse Bayesian learning with automatic relevance determination (ARD) prior is possible. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Ordinal Regression / Logistic Regression / Basis Function / Sparse Bayesian Learning |
| Paper # | IBISML2012-87 |
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| Conference Information | |
| Committee | IBISML |
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| Conference Date | 2012/10/31(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Ordinal Regression Model Based on Logistic Regression Models and Its Fast Sparse Bayesian Learning |
| Sub Title (in English) | |
| Keyword(1) | Ordinal Regression |
| Keyword(2) | Logistic Regression |
| Keyword(3) | Basis Function |
| Keyword(4) | Sparse Bayesian Learning |
| 1st Author's Name | Kazuhisa NAGASHIMA |
| 1st Author's Affiliation | Department of Electrical Engineering and Bioscience, Graduate School of Advanced Science and Engineering, Waseda University() |
| 2nd Author's Name | Masato INOUE |
| 2nd Author's Affiliation | Department of Electrical Engineering and Bioscience, Graduate School of Advanced Science and Engineering, Waseda University |
| Date | 2012-11-08 |
| Paper # | IBISML2012-87 |
| Volume (vol) | vol.112 |
| Number (no) | 279 |
| Page | pp.pp.- |
| #Pages | 5 |
| Date of Issue | |