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: 2

Min number of clusters.

maxClustersInteger, default: 10

Max number of clusters.

restartsInteger, default: 10

Number of restarts.

manualBoolean, default: false

Manually select the number of clusters.

initBoolean, default: false

Set 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: null

Maximum number of iterations for k-means.



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