Adaptive affinity propagation algorithm based on new strategy of dynamic damping factor and preference

2018 ◽  
Vol 14 (1) ◽  
pp. 97-104
Author(s):  
Jiusong Hu ◽  
Hongli Liu ◽  
Zhi Yan
2018 ◽  
Vol 24 (4) ◽  
pp. 426-441 ◽  
Author(s):  
André Fenias Moiane ◽  
Álvaro Muriel Lima Machado

Abstract: The identification of significant underlying data patterns such as image composition and spatial arrangements is fundamental in remote sensing tasks. Therefore, the development of an effective approach for information extraction is crucial to achieve this goal. Affinity propagation (AP) algorithm is a novel powerful technique with the ability of handling with unusual data, containing both categorical and numerical attributes. However, AP has some limitations related to the choice of initial preference parameter, occurrence of oscillations and processing of large data sets. This paper evaluates the clustering performance of AP algorithm taking into account the influence of preference parameter and damping factor. The study was conducted considering the AP algorithm, the adaptive AP and partition AP. According to the experiments, the choice of preference and damping greatly influences on the quality and the final number of clusters.


2015 ◽  
Vol 72 (1) ◽  
pp. 53-61 ◽  
Author(s):  
Eder Jorge de Oliveira ◽  
Fernanda Alves Santana ◽  
Luciana Alves de Oliveira ◽  
Vanderlei da Silva Santos

2013 ◽  
Vol 12 (18) ◽  
pp. 4544-4548 ◽  
Author(s):  
X.H. Chen ◽  
L. Niu ◽  
Y.J. Zhou ◽  
Z. Bi ◽  
G. Ding ◽  
...  

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