DocumentCode
714659
Title
Classification with Lorentzian distance metric
Author
Bilge, Hasan Sakir ; Kerimbekov, Yerzhan
Author_Institution
Bilgisayar Muhendisligi Bolumu, Gazi Univ., Ankara, Turkey
fYear
2015
fDate
16-19 May 2015
Firstpage
2106
Lastpage
2109
Abstract
In this study, a new distance metric that can be used in classification is proposed and its success is investigated. The classification success is increased by using the special distance metric in Lorentzian space. In order to find the optimum angle in transformation from Euclidean space to Lorentzian space, the decision line from Support Vector Machine is utilized. In experimental studies, the success of the proposed method is investigated by using open source data sets; WINE, ECOLI, BLOGGER, DIABET.
Keywords
image classification; support vector machines; visual databases; BLOGGER; DIABET; ECOLI; Euclidean space; Lorentzian distance metric; Lorentzian space; SVM; WINE; decision line; open source data sets; optimum angle; support vector machine; Blogs; Extraterrestrial measurements; Geometry; Scientific computing; Tensile stress; Visualization; Lorentz space; classification; distance measure;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location
Malatya
Type
conf
DOI
10.1109/SIU.2015.7130286
Filename
7130286
Link To Document