使用yellowbrick库进行肘关节可视化。

from sklearn import datasets
from sklearn.cluster import KMeans
from yellowbrick.cluster import KElbowVisualizer

# Load the IRIS dataset
iris = datasets.load_iris()
X = iris.data
y = iris.target

# Instantiate the clustering model and visualizer
km = KMeans(random_state=42)
visualizer = KElbowVisualizer(km, k=(2,10))
 
visualizer.fit(X)        # Fit the data to the visualizer
visualizer.show()        # Finalize and render the figure
elbow_value = visualizer.elbow_value

或者，您可以计算每个失真分数之间的导数，并在导数的变化小于阈值变量时返回手肘值。有关详细信息，请查看此文档。