Variable neighborhood search algorithm for k-means clustering
[摘要] We propose new algorithms of Greedy Heuristic Method for solving the classical problem of cluster analysis, k-Means, which allows us to obtain results with better objective function values in comparison with known algorithms such as k-Means and j-Means. Their comparative efficiency is proved by experiment on various data sets including multidimensional data of non-destructive rejection tests of electronic components for the space industry.
[发布日期] [发布机构] Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy av. 31, Krasnoyarsk; 660037, Russia^1;Krasnoyarsk State Agrarian University, Mira av. 90, Krasnoyarsk; 660049, Russia^2
[效力级别] 工业技术 [学科分类]
[关键词] Classical problems;Comparative efficiencies;Electronic component;Greedy heuristics;K;means clustering;Multidimensional data;Objective function values;Variable neighborhood search [时效性]
