Initial Cluster Centers Based on Moving Two Lines Approximation in K-means Algorithm
DOI:
https://doi.org/10.54097/fcis.v2i1.2488Keywords:
Initial cluster centers, Moving two lines approximation, K-means algorithmAbstract
The main shortcoming of K-means clustering algorithm is its great dependence on the initial cluster center point. Based on the moving two lines approximation model, this paper gives a method to pick the initial cluster center of k-means clustering. Numerical experiments and comparison criteria show that this method can get better clustering effect.
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References
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