from sklearn import datasets
import matplotlib.pyplot as plt
# 制作块数据
x, y = datasets.make_blobs(centers=2, random_state=1)
# 制作双圆环数据
x, y = datasets.make_circles(noise=0.05)
# 制作多分类数据集 | 简化版本为make_blobs
x, y = datasets.make_classification(n_informative=2, n_redundant=0, n_repeated=0, random_state=5)
# 制作交互的半圆
x, y = datasets.make_moons(noise=0.05)
# 制作多目标分类
x, y = datasets.make_multilabel_classification(n_features=2, n_classes=4, n_labels=2)
# _, axes = plt.subplots(2)
# for idx, ax in enumerate(axes):
# ax.axis("off")
# ax.scatter(x[:, 0], x[:, 1], c=y[:, idx], s=50)
# plt.scatter(x[:, 0], x[:, 1], c=y, s=50)
# plt.show()
# 制作线性回归
x, y = datasets.make_regression(n_features=1, n_targets=1, noise=6)
# plt.scatter(x, y)
# plt.show()
