Implemented KMeans
from Util.Util import DataUtil
from i_Clustering.KMeans import KMeans
x, y = DataUtil.gen_two_clusters() # Generate two clusters
k_means = KMeans()
k_means.fit(x) # Train KMeans (n_clusters: 2)
k_means.visualize2d(x, y, dense=400, extra=k_means["centers"])
# Visualize result (2d)
# Rendering KMeans centers by setting 'extra=k_means["centers"]')