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A Relationship Between Generalization Error and Training Samples in Kernel Regressors
Title: | A Relationship Between Generalization Error and Training Samples in Kernel Regressors |
Authors: | Tanaka, Akira Browse this author | Imai, Hideyuki Browse this author | Kudo, Mineichi Browse this author | Miyakoshi, Masaaki Browse this author |
Keywords: | kernel regressor | reproducing kernel Hilbert space | generalization error | sample points |
Issue Date: | 23-Aug-2010 |
Publisher: | IEEE |
Journal Title: | 2010 20th International Conference on Pattern Recognition (ICPR) |
Start Page: | 1421 |
End Page: | 1424 |
Publisher DOI: | 10.1109/ICPR.2010.351 |
Abstract: | A relationship between generalization error and training samples in kernel regressors is discussed in this paper. The generalization error can be decomposed into two components. One is a distance between an unknown true function and an adopted model space. The other is a distance between an estimated function and the orthogonal projection of the unknown true function onto the model space. In our previous work, we gave a framework to evaluate the first component. In this paper, we theoretically analyze the second one and show that a larger set of training samples usually causes a larger generalization error. |
Conference Name: | International Conference on Pattern Recognition (ICPR) |
Conference Sequence: | 20 |
Conference Place: | Istanbul |
Rights: | © 2010 IEEE. Reprinted, with permission, from Akira Tanaka, Hideyuki Imai, Mineichi Kudo, and Masaaki Miyakoshi, A Relationship Between Generalization Error and Training Samples in Kernel Regressors, 2010 International Conference on Pattern Recognition, Aug. 2010. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Hokkaido University products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. |
Type: | proceedings (author version) |
URI: | http://hdl.handle.net/2115/46851 |
Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 田中 章
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