TY - GEN
T1 - Vektör uzaylarinda öznitelik ard arda ekleme yönteminin analizi
AU - Ozay, Mete
AU - Yarman Vural, Fatos T.
PY - 2010/12/1
Y1 - 2010/12/1
N2 - In this study, the theoretical and experimental analysis of feature space concatenation operation is introduced. This operation is widely used for data fusion and ensemble learning. Following the analysis, a new performance measure which is called Vectorization Measure (VM) is introduced. VM enables the estimation of the separability capacity of the fusion space by analyzing the sample margin distributions on the feature vector subpsaces.
AB - In this study, the theoretical and experimental analysis of feature space concatenation operation is introduced. This operation is widely used for data fusion and ensemble learning. Following the analysis, a new performance measure which is called Vectorization Measure (VM) is introduced. VM enables the estimation of the separability capacity of the fusion space by analyzing the sample margin distributions on the feature vector subpsaces.
UR - http://www.scopus.com/inward/record.url?scp=78651434032&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78651434032&partnerID=8YFLogxK
U2 - 10.1109/SIU.2010.5651471
DO - 10.1109/SIU.2010.5651471
M3 - Conference contribution
AN - SCOPUS:78651434032
SN - 9781424496716
T3 - SIU 2010 - IEEE 18th Signal Processing and Communications Applications Conference
SP - 1
EP - 4
BT - SIU 2010 - IEEE 18th Signal Processing and Communications Applications Conference
T2 - 18th IEEE Signal Processing and Communications Applications Conference, SIU 2010
Y2 - 22 April 2010 through 24 April 2010
ER -