import numpy as np

from sklearn import datasets

from sklearn.cluster import KMeans

from sklearn.metrics import *

iris = datasets.load_iris()

centroids = np.array([

[5.006, 3.418, 1.464, 0.244],

[5.9016129, 2.7483871, 4.39354839, 1.43387097],

[6.85, 3.07368421, 5.74210526, 2.07105263],

])

predictor = KMeans(n_clusters=3, init=centroids, n_init=1)

predictor.fit(iris.data)

completeness = completeness_score(iris.target, predictor.labels_)

homogeneity = homogeneity_score(iris.target, predictor.labels_)

accuracy = accuracy_score(iris.target, predictor.labels_)

print("Completeness:", completeness)

print("Homogeneity:", homogeneity)

print("Accuracy:", accuracy)