Method that runs the MiniBatchKmeans algorithm using the Euclidean metric to make an external or internal validation of the cluster
mini_kmeans_method(dt, clusters, columnClass, metric)number of clusters
is an integer with the number of columns, for example if a dataset has five column, we can select column four to calculate validation
metrics avalaible in the package. The metrics implemented are: entropy, variation_information,precision,recall,f_measure, fowlkes_mallows_index,connectivity,dunn,silhouette.
matrix or data frame
returns a list with both the internal and external evaluation of the grouping