[人工智能]knn代码实现

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

values=np.array([
    [0.2,0.2],
    [0.3,0.3],
    [0.4,0.4],
    [0.8,0.8]
])
labels=['A','B','C','D']
# df=pd.DataFrame(values,labels)
# print(df)
axis=sns.scatterplot(x=values[:,0],y=values[:,1])
for value,label in zip(values,labels):
    axis.text(value[0],value[1],label)
for i,j in zip(np.random.random(10),np.random.random(10)):
    knn=KNeighborsClassifier(n_neighbors=2)
    knn.fit(values,labels)
    a=knn.predict([[i,j]])
    a1=np.array([[i,j]])
    print(a1)
    print(a)
    if a=='A':
        axis = sns.scatterplot(x=a1[:,0],y=a1[:,1],color='y')
    else:
        axis = sns.scatterplot(x=a1[:,0],y=a1[:,1],color='r')
    i+=i

plt.show()