DocumentCode :
2979569
Title :
A New Classification Based on the Method of Similitude Compress Convex Hull
Author :
A Lei ; Wu Yuntian ; Wan Fuyong
Author_Institution :
Mathematic Dept., East China Normal Univ., Shanghai, China
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
1
Lastpage :
3
Abstract :
In this paper, we validate the feasibility of similitude compress convex hull, and design a new classification based on the method. And, we give a judgment about two convex hulls´ intersection and other parameters´ estimation. Then we deduce the geometrical bisection method based on similitude compress convex hull. Besides, we present another method for compressing convex hull, and the linear separable SVM based on similitude compressing all points. At last, we give the result of numerical simulation about Iris flower data, shows the high time efficiency and accuracy by the algorithm.
Keywords :
data compression; parameter estimation; pattern classification; support vector machines; geometrical bisection method; iris flower data; linear separable SVM; numerical simulation; parameter estimation; similitude compress convex hull method; Classification algorithms; Electronic mail; Iris; Presses; Statistical learning; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Technology (ICMT), 2010 International Conference on
Conference_Location :
Ningbo
Print_ISBN :
978-1-4244-7871-2
Type :
conf
DOI :
10.1109/ICMULT.2010.5629868
Filename :
5629868
Link To Document :
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