@inproceedings{5b43b5bb077d48d7a36095a96aca4806,
title = "A novel solution scheme for the kernel MSE model",
abstract = "In this paper we first show that the minimum squared-error solutions of kernel minimum squared-error (KMSE) models are neither unique nor numerically stable. We then propose a novel scheme for KMSE. This solution scheme can produce the unique solution and the maximum betweenclass margin. This solution has a highly accurate classification rate. The experimental result illustrates the feasibility and effectiveness of MNMSE solution of KMSE.",
keywords = "Kernel minimum squared error, Modelling, Pattern recognition",
author = "Jinghua Wang",
year = "2009",
doi = "10.1109/AICI.2009.302",
language = "英语",
isbn = "9780769538167",
series = "2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009",
pages = "375--378",
booktitle = "2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009",
note = "2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009 ; Conference date: 07-11-2009 Through 08-11-2009",
}