作业12答案

代码如下

import numpy as np

import matplotlib.pyplot as plt

from sklearn.datasets.samples_generator import make_blobs

center=[[1,1],[-1,-1],[1,-1]]

cluster_std=0.3

X,labels=make_blobs(n_samples=200,centers=center,n_features=2,

                cluster\_std=cluster\_std,random\_state=0\)

print('X.shape',X.shape)

print("labels",set(labels))

unique_lables=set(labels)

colors=plt.cm.Spectral(np.linspace(0,1,len(unique_lables)))

for k,col in zip(unique_lables,colors):

x\_k=X\[labels==k\]

plt.plot\(x\_k\[:,0\],x\_k\[:,1\],'o',markerfacecolor=col,markeredgecolor="k",

         markersize=14\)

plt.title('data by make_blob()')

plt.show()

#生成用于分类的数据集

from sklearn.datasets.samples_generator import make_classification

X,labels=make_classification(n_samples=200,n_features=2,n_redundant=0,n_informative=2,

                         random\_state=1,n\_clusters\_per\_class=2\)

rng=np.random.RandomState(2)

X+=2*rng.uniform(size=X.shape)

unique_lables=set(labels)

colors=plt.cm.Spectral(np.linspace(0,1,len(unique_lables)))

for k,col in zip(unique_lables,colors):

x\_k=X\[labels==k\]

plt.plot\(x\_k\[:,0\],x\_k\[:,1\],'o',markerfacecolor=col,markeredgecolor="k",

         markersize=14\)

plt.title('data by make_classification()')

plt.show()

#生成球形判决界面的数据

from sklearn.datasets.samples_generator import make_circles

X,labels=make_circles(n_samples=200,noise=0.2,factor=0.2,random_state=1)

print("X.shape:",X.shape)

print("labels:",set(labels))

unique_lables=set(labels)

colors=plt.cm.Spectral(np.linspace(0,1,len(unique_lables)))

for k,col in zip(unique_lables,colors):

x\_k=X\[labels==k\]

plt.plot\(x\_k\[:,0\],x\_k\[:,1\],'o',markerfacecolor=col,markeredgecolor="k",

         markersize=14\)

plt.title('data by make_moons()')

plt.show()