README.md
In akinori-ito/successive-binary-partition-kmeans: Successive binary partition k-means algorithm
Successive binary partition k-means
The successive binary partition k-means algorithm. This algorithm divides the largest cluster into two clusters successively until the number of clusters reaches the specified number of clusters. As a result, the cluster sizes are less biased compared with the result of the k-means algorithm.
Ito, A. (2022, July). Successive binary partition k-means method for clustering with less cluster size bias. In 2022 7th International Conference on Signal and Image Processing (ICSIP) (pp. 772-776). IEEE.
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Successive binary partition k-means
The successive binary partition k-means algorithm. This algorithm divides the largest cluster into two clusters successively until the number of clusters reaches the specified number of clusters. As a result, the cluster sizes are less biased compared with the result of the k-means algorithm.
Ito, A. (2022, July). Successive binary partition k-means method for clustering with less cluster size bias. In 2022 7th International Conference on Signal and Image Processing (ICSIP) (pp. 772-776). IEEE.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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