三维图形Python

import numpy as np

import matplotlib.pyplot as plt

from sklearn.datasets import load_breast_cancer

from mpl_toolkits.mplot3d import Axes3D

from sklearn.decomposition import TruncatedSVD

 

#加载数据集

data = load_breast_cancer()

X = data.data

y = data.target

 

# 进行降维处理，保留3个主成分

svd = TruncatedSVD(n_components=3)

X_reduce = svd.fit_transform(X)

 

#创建三维图形

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

 

 

#根据目标标签设置不同的颜色

colors = ['r' if label == 0 else 'b' for label in y]

 

#绘制散点图

ax.scatter(X_reduce[:, 0], X_reduce[:, 1], X_reduce[:, 2], c=colors)

 

#设置轴标签

ax.set_xlabel('Component 1')

ax.set_ylabel('Component 2')

ax.set_zlabel('Component 3')

 

#显示图形

plt.show()