SACOC:A Spectral-Based ACO Clustering Algorithm [chapter]

Héctor D. Menéndez, Fernando E. B. Otero, David Camacho
2015 Studies in Computational Intelligence  
The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning have been focused on clustering, where ACO-based techniques have showed a great potential. At the same time, new clustering techniques that seek the continuity of data, specially focused on spectral-based approaches in opposition to classical
more » ... ntroid-based approaches, have attracted an increasing research interest-an area still under study by ACO clustering techniques. This work presents a hybrid spectralbased ACO clustering algorithm inspired by the ACO Clustering (ACOC) algorithm. The proposed approach combines ACOC with the spectral Laplacian to generate a new search space for the algorithm in order to obtain more promising solutions. The new algorithm, called SACOC, has been compared against well-known algorithms (K-means and Spectral Clustering) and with ACOC. The experiments measure the accuracy of the algorithm for both synthetic datasets and real-world datasets extracted from the UCI Machine Learning Repository.
doi:10.1007/978-3-319-10422-5_20 fatcat:n5zgfmgkbfbrzasdstperx7l6m