Title :
A Symmetrical Linear Transform Learning Algorithm on Quantum Group
Author :
He, Shuping ; Li, Fanzhang
Author_Institution :
Soochow Univ., Suzhou
Abstract :
Based on Lie group machine learning theory and noncommutative features of quantum group, this paper proposes a symmetrical linear transform learning algorithm on quantum group and have it applied on DNA sequence classification. The comparing between quantum group classifier and the widely used SVM is also presented.
Keywords :
DNA; Lie groups; biology computing; learning (artificial intelligence); pattern classification; quantum theory; sequences; support vector machines; transforms; DNA sequence classification; Lie group theory; SVM; machine learning; quantum group; symmetrical linear transform learning algorithm; Algebra; Computer science; DNA; Geometry; Helium; Machine learning; Machine learning algorithms; Quantum computing; Quantum mechanics; Sequences;
Conference_Titel :
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3032-1
DOI :
10.1109/GrC.2007.37
