DocumentCode :
2657470
Title :
Softmax Discriminant Classifier
Author :
Zang, Fei ; Zhang, Jiang-she
Author_Institution :
State Key Lab. for Manuf. Syst. Eng., Xi´´an Jiaotong Univ., Xi´´an, China
fYear :
2011
fDate :
4-6 Nov. 2011
Firstpage :
16
Lastpage :
19
Abstract :
A simple but effective classifier, which is called soft max discriminant classifier or SDC for short, is presented. Based on the soft max discriminant function, SDC assigns the label information to a new testing sample by nonlinear transformation of the distance between the testing sample and training samples. Experimental results on some well-known data sets demonstrate the feasibility and effectiveness of the proposed algorithm.
Keywords :
pattern classification; SDC; nonlinear transformation; softmax discriminant classifier; Accuracy; Educational institutions; Glass; Pattern recognition; Principal component analysis; Testing; Training; classifier; nonlinear transformation; softmax discriminant function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Information Networking and Security (MINES), 2011 Third International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-1795-6
Type :
conf
DOI :
10.1109/MINES.2011.123
Filename :
6103712
Link To Document :
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