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https://ah.nccu.edu.tw/handle/140.119/120196
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Title: | Trust region Newton method for large-scale logistic regression. |
Authors: | Lin, Chih-Jen;Weng, Ruby C.;Keerthi, S. Sathiya 翁久幸 Weng, Ruby C. |
Contributors: | 應數系 |
Date: | 2007 |
Issue Date: | 2018-09-28 16:30:04 (UTC+8) |
Abstract: | Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method to maximize the log-likelihood of the logistic regression model. The proposed method uses only approximate Newton steps in the beginning, but achieves fast convergence in the end. Experiments show that it is faster than the commonly used quasi Newton approach for logistic regression. We also compare it with linear SVM implementations. |
Relation: | Journal of Machine Learning Research , 9, 627-650 AMS MathSciNet:MR2417250 |
Data Type: | article |
DOI 連結: | http://dx.doi.org/10.1145/1273496.1273567 |
Appears in Collections: | [應用數學系] 期刊論文 |
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