python中K-means算法是什么？

km = KMeans(n_clusters = 3)

km.fit(X)

centers = km.cluster_centers_

print(centers)

[[5.006      3.428     ]

 [6.81276596 3.07446809]

 [5.77358491 2.69245283]]

predicted_labels = km.labels_

fig, axes = plt.subplots(1, 2, figsize=(16,8))

axes[0].scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Set1,

                edgecolor='k', s=150)

axes[1].scatter(X[:, 0], X[:, 1], c=predicted_labels, cmap=plt.cm.Set1,

                edgecolor='k', s=150)

axes[0].set_xlabel('Sepal length', fontsize=16)

axes[0].set_ylabel('Sepal width', fontsize=16)

axes[1].set_xlabel('Sepal length', fontsize=16)

axes[1].set_ylabel('Sepal width', fontsize=16)

axes[0].tick_params(direction='in', length=10, width=5, colors='k', labelsize=20)

axes[1].tick_params(direction='in', length=10, width=5, colors='k', labelsize=20)

axes[0].set_title('Actual', fontsize=18)

axes[1].set_title('Predicted', fontsize=18)