Exact k-Medoids Functionality#

Descriptions of the basic functions are given below.

Function descriptions:

class k_medoids_exact.KMedoids(n_clusters=8, distance_metric='euclidean', timelimit=100, threads=7, solver='highs')[source]#

k-medoids class.

Parameters:

  • n_clusters (integer) – How many medoids. Must be positive. optional, default: 8

  • distance_metric (string) – What distance metric to use. optional, default: ‘euclidean’

  • timelimit (integer) – Specify the time limit of the solver. optional, default: 100

  • threads (integer) – Threads to use by the optimization solver. optional, default: 7

  • solver (string) – Specifies the solver. optional, default: ‘highs’

fit(X, y=None)[source]#

Fit K-Medoids to the provided data.

Parameters:

X (array-like or sparse matrix) – shape=(n_samples, n_features)

Returns:

self