k-means算法（使用包）

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

X爲樣本特徵，Y爲樣本簇類別， 共1000個樣本，每一個樣本4個特徵，共4個簇，簇中心在[-1,-1], [0,0],[1,1], [2,2]， 簇方差分別爲[0.4, 0.2, 0.2]

X, y = make_blobs(n_samples=1000, n_features=2, centers=[[-1,-1], [0,0], [1,1], [2,2]], cluster_std=[0.4, 0.2, 0.2, 0.2], random_state =9) plt.scatter(X[:, 0], X[:, 1], marker='o') plt.show()

y_pred = KMeans(n_clusters=4, random_state=9).fit_predict(X) plt.scatter(X[:, 0], X[:, 1], c=y_pred) plt.show()