sil = []
for i in range(2,11):
kmeans= KMeans(n_clusters=i,init='k-means++',random_state=123) # 分成2-10群，分别计算silhouette值，画图
y_kmeans = kmeans.fit_predict(target_value.reshape(-1,1))
sil.append(metrics.silhouette_score(target_value.reshape(-1,1),y_kmeans))
print(i)
plt.plot(range(2,11),sil)
plt.title('The Silhouette Method')
plt.xlabel('Number of clusters')
plt.ylabel('Silhouette Coefficient')
plt.show()
