n_samples = 1500

# 生成噪声圆
X_noisy_circles, y_noisy_circles = datasets.make_circles(n_samples=n_samples, factor=.5, noise=.05)

# 月亮型的噪声数据
X_noisy_moons,y_noisy_moons = datasets.make_moons(n_samples=n_samples, noise=.05)

# 高斯数据，方差默认为1的高斯数据
X_blobs,y_blobs = datasets.make_blobs(n_samples=n_samples, random_state=8)

# 针对不同的高斯分布设置方差
X_blobs_varied,y_blobs_varied = datasets.make_blobs(n_samples=n_samples,
                             cluster_std=[1.0, 2.5, 0.5],
                             random_state=random_state)
# 设置每个维度方向上的不同方差的高斯分布
random_state = 170
X, y_aniso = datasets.make_blobs(n_samples=n_samples, random_state=random_state)
transformation = [[0.6, -0.6], [-0.4, 0.8]]
X_aniso = np.dot(X, transformation)