Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

@article{Celebi2014LinearDA,
  title={Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm},
  author={M. Emre Celebi and Hassan A. Kingravi},
  journal={CoRR},
  year={2014},
  volume={abs/1409.3854}
}
Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity , time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous… CONTINUE READING