Research of the Symplectic Group Classifier Based on Lie Group Machine Learning

This paper describes the theories of symplectic group based on the basic conceptions and theory framework of lie group machine learning (LML), it implements the constructor of symplectic classifier in Lie group machine learning (LML), along with the descriptions of the correlated problems. This cont...

Full description

Saved in:
Bibliographic Details
Published inFourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) Vol. 1; pp. 649 - 654
Main Authors Huixin Fu, Fanzhang Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2007
Subjects
Algebra
Computer science
Data processing
Finite element methods
Geometry
Learning systems
Machine learning
Multidimensional systems
Principal component analysis
System testing
Online AccessGet full text

Cover

More Information
Summary:This paper describes the theories of symplectic group based on the basic conceptions and theory framework of lie group machine learning (LML), it implements the constructor of symplectic classifier in Lie group machine learning (LML), along with the descriptions of the correlated problems. This contained by: mapping the observed data set in the learning system to the nonempty set G; constructing the corresponding symplectic group structure according to G; applying the obtained symplectic group to the lie group machine learning (LML) model; and forming the symplectic classifiers; testing examples and giving performance results.
ISBN:9780769528748
0769528740
DOI:10.1109/FSKD.2007.469