Description Usage Arguments Value Author(s) See Also Examples
Find Cluster model using White-Box Cluster Algorithm Design.
1 2 3 | whibo_clustering(data, k = 3, normalization_type = "No",
cluster_initialization_type = "Random", assignment_type = "Euclidean",
recalculation_type = "Mean", max_iteration = 20, no_of_restarts = 1)
|
data |
Data on which clustering should be performed. |
k |
Number of Cluster Representatives. |
normalization_type |
Which normalization should be used (look at |
cluster_initialization_type |
Which initialization of Cluster Representatives should be used (look at |
assignment_type |
Which assignment function should be used (look at |
recalculation_type |
Which function for updating Cluster Representatives should be used (look at |
max_iteration |
Number of iterations. Default value is 20. |
no_of_restarts |
Number of restarts of whole clustering procedure. Default value is 1. |
Object of type whibo_cluster
which include Cluster Representatives (centroids
), number of elements per cluster (elements_per_cluster
), assignments (assignments
), measures of cluster quality (within_sum_of_squares
, between_ss_div_total_ss
and internal_measures_of_quality
), cluster models per iterations (model_history
), iterations (iterations
) and parameters used (params
)
Sandro Radovanovic sandro.radovanovic@gmail.com
plot.whibo_cluster
, predict.whibo_cluster
1 2 3 4 5 6 7 8 9 10 | data <- iris[, 1:4] #Take only numerical columns
#Perform k-means clustering
model <- whibo_clustering(data = data, k = 3)
model
#Perform some unorthodox clustering
model <- whibo_clustering(data = data, k = 3,
normalization_type = 'Z', cluster_initialization_type = 'Ward',
assignment_type = 'Correlation', recalculation_type = 'Trimean')
|
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