使用forge数据集，分别对近邻K=1,3,9进行对比分析决策边界。

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import mglearn
from sklearn.neighbors import KNeighborsClassifier

X,y=mglearn.datasets.make_forge()

fig,axes=plt.subplots(1,3,figsize=(10,3))
for n_neighbors,ax in zip([1,3,9],axes):
    clf=KNeighborsClassifier(n_neighbors=n_neighbors).fit(X,y)
    mglearn.plots.plot_2d_separator(clf,X,fill=True,eps=0.5,ax=ax,alpha=.4)
    mglearn.discrete_scatter(X[:,0],X[:,1],y,ax=ax)
    ax.set_title("{} neighbors".format(n_neighbors))
    ax.set_xlabel("feature 0")
    ax.set_ylabel("feature 1")
axes[0].legend(loc=3)

输出结果如下图所示：

image.png