“KMeans”对象没有属性“cluster_centers_”答案

【问题标题】：'KMeans' object has no attribute 'cluster_centers_'“KMeans”对象没有属性“cluster_centers_”
【发布时间】：2020-11-03 01:13:08
【问题描述】：

我正在使用 Jupyter 笔记本，我编写了以下代码：

from sklearn.datasets import make_blobs
dataset = make_blobs(n_samples=200, centers = 4,n_features = 2, cluster_std = 1.6, random_state = 50)
points = dataset[0];
from sklearn.cluster import KMeans
kmeans = KMeans(n_clusters = 4)
kmeans.fit(points)
plt.scatter(dataset[0][:,0],dataset[0][:,1])
clusters = kmeans.cluster_centers_

// 下面一行给出了错误：'KMeans' object has no attribute 'cluster_centers_'

clusters = kmeans.cluster_centers_

我期待它显示点的平均值或平均值。

【问题讨论】：

标签： python k-means

【解决方案1】：

在您的示例中不清楚您的语句是在您致电 fit 之前还是之后。该属性在fit 方法中定义。你是在fit 之前还是之后调用你的函数？

如果你这样做，会有一个错误：

from sklearn.datasets import make_blobs
import matplotlib.pyplot as plt

dataset = make_blobs(n_samples=200, centers = 4,n_features = 2, cluster_std = 1.6, random_state = 50)
points = dataset[0]

from sklearn.cluster import KMeans
kmeans = KMeans(n_clusters=4)
clusters = kmeans.cluster_centers_
kmeans.fit(points)

plt.scatter(dataset[0][:,0],dataset[0][:,1])

但是这种方式不会产生错误

from sklearn.datasets import make_blobs
import matplotlib.pyplot as plt

dataset = make_blobs(n_samples=200, centers = 4,n_features = 2, cluster_std = 1.6, random_state = 50)
points = dataset[0]

from sklearn.cluster import KMeans
kmeans = KMeans(n_clusters=4)
kmeans.fit(points)
clusters = kmeans.cluster_centers_

plt.scatter(dataset[0][:,0],dataset[0][:,1])

【讨论】：