An Optimized k-means Algorithm for Selecting Initial Clustering Centers

@article{Song2015AnOK,
  title={An Optimized k-means Algorithm for Selecting Initial Clustering Centers},
  author={Jianhui Song and Xuefei Li and Yanju Liu},
  journal={International journal of security and its applications},
  year={2015},
  volume={9},
  pages={177-186}
}
Selecting the initial clustering centers randomly will cause an instability final result, and make it easy to fall into local minimum. To improve the shortcoming of the existing kmeans clustering center selection algorithm, an optimized k-means algorithm for selecting initial clustering centers is proposed in this paper. When the number of the sample’s maximum density parameter value is not unique, the distance between the plurality samples with maximum density parameter values is calculated… 

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