相关疑难解决方法(0)

我试图用颜色和正确的标签表示预测，以作为虹膜数据集的标记。这是我到目前为止的内容：

from sklearn.mixture import GMM
import pandas as pd
from sklearn import datasets
import matplotlib.pyplot as plt
import itertools

iris = datasets.load_iris()
x = iris.data
y = iris.target
gmm = GMM(n_components=3).fit(x)
labels = gmm.predict(x)
fig, axes = plt.subplots(4, 4)
Superman = iris.feature_names
markers = ["o" , "s" , "D"]
Mi=[]
for i in range(150):
  Mi.append(markers[y[i]])

for i in range(4):
    for j in range(4):
        if(i != j):
            axes[i, j].scatter(x[:, i], x[:, j], c=labels, marker = Mi, s=40, cmap='viridis')
        else:
            axes[i,j].text(0.15, 0.3, …

我想展示一些观点.这是我的代码:

plt.scatter(y[:,0],y[:,1],c=col)
plt.show()

就像col我一样:

Col:  [1 1 0 1 1 1 1 0 0 0 1 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 0 1 1 0 1 1 0 0 0 0
 0 0 0 0 0 0 0 1 1 0 1 1 0 1 0 0 1 0 1 1 0 1 0 1 0 0 1 1 1 1 1 1 1 1 1 0 …