Title :
Pattern recognition based on the minimum norm minimum squared-error classifier
Author :
Song, Fengxi ; Yang, Jingyu ; Liu, Shuhai
Author_Institution :
Dept. of Comput. Sci. Technol., Nanjing Univ. of Sci. &, China
Abstract :
The performance of a novel binary linear classifier named as minimum norm minimum squared-error (MNMSE), which is based on a refined minimum squared-error discriminant criterion is evaluated in this paper. Experimental results show that MNMSE is very effective and efficient for many pattern recognition problems. In most cases it can compete with support vector machines in recognition rate and be more efficient than the methods.
Keywords :
least mean squares methods; pattern classification; support vector machines; binary linear classification; minimum norm minimum squared-error classification; minimum squared-error discriminant criterion; pattern recognition; support vector machines; Algorithm design and analysis; Computational efficiency; Computer science; Equations; Face recognition; Matrices; Pattern recognition; Statistical analysis; Support vector machine classification; Support vector machines;
Conference_Titel :
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN :
0-7803-8653-1
DOI :
10.1109/ICARCV.2004.1469000
