This function takes a gama object and prints:
a sample of the original dataset used for clustering;
the cluster solution (partitions);
the centers of partitions;
the indices Average Silhouette Width (ASW), Calinski Harabasz (CH), C-Index (CI), Dunn index (DI).
an object of type 'gama' generated by an appropriate call to the clustering algorithm.
other arguments that user may pass to the function.
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## Not run: # loads data about CPU execution metrics of a distributed # version of Alternating Least Squares (ALS) algorithm data(cpu.als) # call the gama clustering algorithm gamaObj <- gama(cpu.als, k = 4) # call the print.gama function to detail the clustering results # note: print.gama uses generic function concept, which allows a call to print, only. print(gamaObj) ## End(Not run)
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