similar_posts.py 文件源码

def elbowMethod(X, k=21):
    distortions = []
    for i in range(1, k):
        km2 = KMeans(n_clusters=i,
                     init='k-means++',
                     n_init=10,
                     random_state=0,
                     n_jobs=-1,
                     verbose=0)
        km2.fit(X)
        distortions.append(km2.inertia_)
        print('k=%s, Distortion: %.2f' % (i, km2.inertia_))

    plt.plot(range(1, k), distortions, marker='o')
    plt.xlabel('Number of clusters')
    plt.ylabel('Distortion')
    plt.show()