机器学习：对鸢尾花数据进行PCA降维后使用k

先附上代码

import matplotlib.pyplot as plt

import numpy as np

from sklearn.cluster import KMeans

from sklearn.datasets import load_iris

from sklearn.decomposition import PCA

iris = load_iris()

X = iris.data

marker="点的形状"

labal="点的标签"

plt.scatter(X[:, 0], X[:, 1], c="black", marker='o',

label='see')

plt.xlabel('petal length')

plt.ylabel('petal width')

plt.title("Data")

plt.show()

kmeans=KMeans(n_clusters=3)

kmeans.fit(X)

y_kmeans=kmeans.predict(X)

x0 = X[y_kmeans == 0]

x1 = X[y_kmeans == 1]

x2 = X[y_kmeans == 2]

plt.scatter(x0[:, 0], x0[:, 1], c="red", marker='o',

label='label0')

plt.scatter(x1[:, 0], x1[:, 1],