kmeans.py

import matplotlib.pyplot as plt
from sklearn.datasets.samples_generator import make_blobs
from sklearn.cluster import KMeans

# Anda dapat mengganti nilai X dan y sesuai dengan kebutuhan Anda
X, y = make_blobs(n_samples=300, centers=4,
                       cluster_std=1.2, random_state=3)

inertia = []
for k in range(1,11):
    kmeans = KMeans(n_clusters=k)
    kmeans.fit(X)
    inertia.append(kmeans.inertia_)
plt.plot(range(1,11), inertia, c='orange', zorder=1)
plt.scatter(range(1,11), inertia, zorder=2)
plt.xlabel('$k$')
plt.ylabel('jarak agregat')
plt.savefig('scree.png')