Clustering Animator

Clustering Animator visualizes/simulates different variations of K-Means algorithm using different datasets. It shows how these algorithms work. You can also point out some advanrages or disadvantages of these algorithms by looking at their simulations or by interacting with them.

References:

P. Fränti and S. Sieranoja, "How much k-means can be improved by usingbetter initialization and repeats?", Pattern Recognition, 93, 95-112, 2019.

P. Fränti, "Efficiency of random swap clustering", Journal of Big Data, 5:13, 1-29, 2018.

M.I. Malinen, R. Mariescu-Istodor and P. Fränti, "K-means*: clustering by gradual data transformation", Pattern Recognition, 47 (10), 3376-3386, October 2014.