Title :
Matrix Similarity Measurement Used in a GA-Based Feature Extraction
Author :
Zhefu, Yu ; Huibiao, Lu ; Chuanying, Jia
Author_Institution :
Dalian Maritime Univ., Dalian, China
Abstract :
A GA-based feature extraction method was presented for solving non-linear regression questions. The order of regression function is determined by practical experience, so the application of this method is limited. In this paper, the angle measurement method of matrix similarity was used to determine the order of the polynomial space. By doing this, the GA-based feature extraction method became more practical. An explicit non-linear regress function can be very easy to find. The experiment shows that it achieved satisfactory results.
Keywords :
feature extraction; genetic algorithms; matrix algebra; nonlinear functions; regression analysis; support vector machines; GA based feature extraction method; genetic algorithm; matrix similarity measurement; nonlinear regression function; polynomial space; Automation; Extraterrestrial measurements; Feature extraction; Genetic algorithms; Goniometers; Kernel; Polynomials; Symmetric matrices; Angle Measurement; Feature Extraction; Genetic Algorithm; Matrix Similarity; Support Vector Regression;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.613