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Cascade simple k-means, selects the best k according to the Calinski-Harabasz criterion. For more information see:

Calinski, T. and J. Harabasz. 1974. A dendrite method for cluster analysis. Commun. Stat. 3: 1-27.

ee.Clusterer.wekaCascadeKMeans(minClusters, maxClusters, restarts, manual, init, distanceFunction, maxIterations)Clusterer
minClustersInteger, default: 2Min number of clusters.
maxClustersInteger, default: 10Max number of clusters.
restartsInteger, default: 10Number of restarts.
manualBoolean, default: falseManually select the number of clusters.
initBoolean, default: falseSet whether to initialize using the probabilistic farthest first like method of the k-means++ algorithm (rather than the standard random selection of initial cluster centers).
distanceFunctionString, default: "Euclidean"Distance function to use. Options are: Euclidean & Manhattan
maxIterationsInteger, default: nullMaximum number of iterations for k-means.