Improved multiple matrix classifier with five kinds of sample information-Reference-Cited by-同舟云学术

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Improved multiple matrix classifier with five kinds of sample information

Published:2019-04-26 Issue:3 Volume:11 Page:421-434
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Zhu Changming^ORCID

Funder

Natural Science Foundations of Shanghai

National Natural Science Foundations of China

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

http://link.springer.com/content/pdf/10.1007/s41870-019-00308-8.pdf

Reference39 articles.

1. Blake CL, Newman DJ, Hettich S, Merz CJ (2012) UCI repository of machine learning databases

2. Chen S, Zhang CS (2009) Selecting informative universum sample for semi-supervised learning. International Jont Conference on Artifical Intelligence 1016–1021

3. Chen SC, Wang Z, Tian YJ (2007) Matrix-pattern-oriented ho-kashyap classifier with regularization learning. Pattern Recognit 40(5):1533–1543

4. Chen XH, Chen SC, Xue H (2012) Universum linear discriminant analysis. Electron Lett 48(22):1407–1409

5. Cherkassky V, Dai WY (2009) Empirical study of the universum SVM learning for high-dimensional data. Lecture Notes Comput Sci 5768:932–941

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