kmeans 簇号与 k 值不匹配

Question

基于 this article 的代码在我仅定义 3 个集群时按预期工作。但是当我改变簇的数量时，我没有得到相同数量的簇。

from matplotlib import image as img
from matplotlib import pyplot as plt
import pandas as pd

image = img.imread("my_logo1.jpg")
image.shape

r = []
g = []
b = []

for line in image:
    for pixel in line:
        temp_r, temp_g, temp_b = pixel
        r.append(temp_r / 255)
        g.append(temp_g / 255)
        b.append(temp_b / 255)

df = pd.DataFrame({"red": r, "green": g, "blue": b})

from scipy.cluster.vq import kmeans
cluster_centers, distortion = kmeans(df[["red", "green", "blue"]], 7)

print(cluster_centers)

cluster centers returned are only 3, expected 7

我希望 return 返回与 kmeans 函数中定义的相同数量的颜色。

Answer 1

正在阅读 kmeans() function, you can note the use of a supporting function _kmeans() 的源代码，您可以在其中找到：

code_book = code_book[has_members]

has_members is a boolean array indicating which clusters have members, resulting from _vq.update_cluster_means().

简而言之，当您指定簇数k时，算法returns一组质心（最多k ) 失真最低。在 K-means 的 update-step 期间简单地删除空簇。

kmeans 簇号与 k 值不匹配

kmeans cluster number does not match with k value

python

machine-learning

scipy

k-means

python-3.x