Variable neighborhood search algorithm for k-means clustering

Viktor I. Orlov, Lev Aleksandrovich Kazakovtsev, Ivan P. Rozhnov, N A Popov, В В Федосов · IOP Conference Series Materials Science and Engineering · 2018

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.

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