ee.Clusterer.wekaCascadeKMeans

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.

Usage	Returns
`ee.Clusterer.wekaCascadeKMeans(minClusters, maxClusters, restarts, manual, init, distanceFunction, maxIterations)`	Clusterer

Argument	Type	Details
`minClusters`	Integer, default: 2	Min number of clusters.
`maxClusters`	Integer, default: 10	Max number of clusters.
`restarts`	Integer, default: 10	Number of restarts.
`manual`	Boolean, default: false	Manually select the number of clusters.
`init`	Boolean, 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).
`distanceFunction`	String, default: "Euclidean"	Distance function to use. Options are: Euclidean & Manhattan
`maxIterations`	Integer, default: null	Maximum number of iterations for k-means.

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Last updated 2023-10-06 UTC.