Cluster analysis using optimization algorithms with newly designed objective functions
作者：
Highlights：
• Perform cluster analysis using three newly designed objective functions.
• Utilize three optimization algorithms like, genetic, cuckoo search and PSO.
• Present 21 different clustering algorithms and the validation with 16 datasets.
• Proved, objective function decides effectiveness & search algorithm decides efficiency.
• Presented a suggestion for a better algorithm based on input data characteristics.
摘要
•Perform cluster analysis using three newly designed objective functions.•Utilize three optimization algorithms like, genetic, cuckoo search and PSO.•Present 21 different clustering algorithms and the validation with 16 datasets.•Proved, objective function decides effectiveness & search algorithm decides efficiency.•Presented a suggestion for a better algorithm based on input data characteristics.
论文关键词：Clustering,Optimization,Genetic algorithm (GA),Cuckoo search (CS),Particle swarm optimization (PSO),Kernel space
论文评审过程：Available online 8 April 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.03.031
