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第三章:支持向量机及其他
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第三章:支持向量机及其他
课件
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推荐读物
Corinna Cortes and Vladimir Vapnik, 1995.
Support-Vector Networks
.
Machine Learning
, Vol. 20, No. 3, pp. 273-297.
John Shawe-Taylor and Nello Cristianini, 2004.
Kernel Methods for Pattern Analysis
. Cambridge University Press.
Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin, 2010.
A Practical Guide to Support Vector Classfication
.
Antti Airola, Sampo Pyysalo, Jari Björne, Tapio Pahikkala, Filip Ginter, and Tapio Salakoski, 2008.
All-Paths Graph Kernel for Protein-Protein Interaction Extraction with Evaluation of Cross-Corpus Learning
.
BMC Bioinformatics
, Vol. 9, No. Suppl 11, pp. S2.
PDF
Shuo Xu, Xin An, Xiaodong Qiao, and Lijun Zhu, 2014.
Multi-Task Least-Squares Support Vector Machines
.
Multimedia Tools and Applications
, Vol. 71, No. 2, pp. 699-715.
PDF
code
Ryan Rifkin, Gene Yeo, and Tomaso Poggio, 2003. Chapter 7: Regularized Least-Squares Classification. Advances in Learning Theory: Methods, Models and Applications.
PDF
Shuo Xu, Xin An, Xiaodong Qiao, Lijun Zhu, and Lin Li, 2013.
Multi-Output Least-Squares Support Vector Regression Machines
.
Pattern Recognition Letters
, Vol. 34, No. 9, pp. 1078-1084.
code
Shuo Xu and Xin An, 2019.
ML2S-SVM: Multi-Label Least-Squares Support Vector Machine Classifiers
.
The Electronic Library
, Vol. 37, No. 6, pp. 1040-1058.
code
Note
Xin An, Yali Wen, Yaoqi Zhang, and Shuo Xu, 2019.
Evaluation of the Forestry and Environmental Conservation Policies in Western China with Multi-Output Regression Method
.
Computers and Electronics in Agriculture
, Vol. 157, pp. 239-246.
Shuo Xu, Liyuan Hao, Xin An, Guancan Yang, and Feifei Wang, 2019.
Emerging Research Topics Detection with Multiple Machine Learning Models
.
Journal of Informetrics
, Vol. 13, No. 4, pp. 100983.
Note
Xin An, Xin Sun, Shuo Xu, Liyuan Hao, and Jinghong Li, 2022.
Important Citations Identification by Exploiting Generative Model into Discriminative Model
.
Journal of Information Science
, Vol. 49, No. 1, pp. 107-121.
Note
Xin An, Xin Sun, and Shuo Xu, 2022.
Important Citations Identification with Semi-Supervised Classification Model
.
Scientometrics
, Vol. 127, No. 11, pp. 6533-6555.
Note