print.gama: Prints results of a Gama clustering.

In jairsonrodrigues/gama: Genetic Approach to Maximize Clustering Criterion

Description

This function takes a gama object and prints:

1. a sample of the original dataset used for clustering;

2. the cluster solution (partitions);

3. the centers of partitions;

4. the indices Average Silhouette Width (ASW), Calinski Harabasz (CH), C-Index (CI), Dunn index (DI).

Usage

 ## S3 method for class 'gama'
print(x, ...)

Arguments

x	an object of type 'gama' generated by an appropriate call to the clustering algorithm.
...	other arguments that user may pass to the function.

See Also

gama, gama.plot.partitions.

Examples

## 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)

jairsonrodrigues/gama documentation built on May 17, 2019, 3:12 a.m.