18029100040吴程锴-第四次上机作业1
需积分: 0 198 浏览量
2022-08-03
12:05:46
上传
评论
收藏 367KB PDF 举报
第三次上机作业
18029100040
吴程锴
一、作业 26：PCA 实现高维数据可视化：
1.1
代码
1. import matplotlib.pyplot as plt
2. from sklearn.decomposition import PCA
3. from sklearn.datasets import load_iris
4. data = load_iris()
5. y = data.target
6. x = data.data
7. pca = PCA(n_components = 2)
8. reduced_x = pca.fit_transform(x)
9. red_x,red_y = [],[]
10. blue_x,blue_y = [],[]
11. green_x,green_y = [],[]
12. for i in range(len(reduced_x)):
13. if y[i] == 0:
14. red_x.append(reduced_x[i][0])
15. red_y.append(reduced_x[i][1])
16. elif y[i] == 1:
17. blue_x.append(reduced_x[i][0])
18. blue_y.append(reduced_x[i][1])
19. else:
20. green_x.append(reduced_x[i][0])
21. green_y.append(reduced_x[i][1])
22. plt.scatter(red_x,red_y, c = 'r',marker = 'x')
23. plt.scatter(blue_x,blue_y, c = 'b',marker = 'D')
24. plt.scatter(green_x,green_y, c = 'g',marker = '.')
25. plt.show()
剩余11页未读，继续阅读
评论0