TY - JOUR
T1 - Subspace clustering using affinity propagation
AU - Gan, Guojun
AU - NG, Kwok Po
N1 - Publisher Copyright:
© 2014 Elsevier Ltd. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2015/4/1
Y1 - 2015/4/1
N2 - This paper proposes a subspace clustering algorithm by introducing attribute weights in the affinity propagation algorithm. A new step is introduced to the affinity propagation process to iteratively update the attribute weights based on the current partition of the data. The relative magnitude of the attribute weights can be used to identify the subspaces in which clusters are embedded. Experiments on both synthetic data and real data show that the new algorithm outperforms the affinity propagation algorithm in recovering clusters from data.
AB - This paper proposes a subspace clustering algorithm by introducing attribute weights in the affinity propagation algorithm. A new step is introduced to the affinity propagation process to iteratively update the attribute weights based on the current partition of the data. The relative magnitude of the attribute weights can be used to identify the subspaces in which clusters are embedded. Experiments on both synthetic data and real data show that the new algorithm outperforms the affinity propagation algorithm in recovering clusters from data.
KW - Affinity propagation
KW - Attribute weighting
KW - Data clustering
KW - Subspace clustering
UR - http://www.scopus.com/inward/record.url?scp=84920672964&partnerID=8YFLogxK
U2 - 10.1016/j.patcog.2014.11.003
DO - 10.1016/j.patcog.2014.11.003
M3 - Journal article
AN - SCOPUS:84920672964
SN - 0031-3203
VL - 48
SP - 1455
EP - 1464
JO - Pattern Recognition
JF - Pattern Recognition
IS - 4
ER -