Open AccessA clustering algorithm based on the combination of screening strategy and swarm
Author(s) -
yudifei
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1616/1/012006
Subject(s) - cluster analysis , cure data clustering algorithm , canopy clustering algorithm , correlation clustering , computer science , data stream clustering , outlier , data mining , algorithm , artificial intelligence , pattern recognition (psychology)
aiming at the problem that the k-means clustering algorithm is affected by the initial clustering center, a k-means clustering optimization algorithm combining the screening strategy and artificial colony (ABC) was proposed.This algorithm operates in an unsupervised way, separating data from outlier points through screening, combining the advantages of ABC algorithm, using the objective function of ABC algorithm as the measurement function of initial clustering, and improving the effectiveness and accuracy of k-means clustering by changing the initial clustering center.