Adaptive affinity propagation method based on improved cuckoo search

Abstract

Affinity propagation (AP) is an efficient clustering technique to deal with datasets of many instances; however, it has oscillations and its preference value needs to be preset. This study proposes an improved cuckoo search (ICS) technique to solve the AP model. The ICS algorithm utilizes quaternions to represent individuals that are to be optimized. The variable step length of Lévy flights and a method of discovering probability are also proposed. The proposed adaptive AP based on ICS is utilized (or tested) to identify four standard test datasets, such as face images and handwritten digits. The proposed method produces highly accurate results.