from sklearn.neighbors.KNneighborsClassifier(n_neighnprs = 5)
from sklearn.neighbors import KNneighborsClassifier
import warings

warings.filterwarnings('ignore')
'''
def dm01_knnapi_Classifier():
    estimator = KNneighborsClassifier(n_neighnprs =1)
    
    x = random.randomint(0,5)
    y = [0,0,1,1]
    
    # 实例化API
    estimator = KNeighborsClassifier(n_neighbors=3)
    # 使用fit法进行训练
    estimator.fit(x, y)
    estimator.predict([1])
    
'''
x = [[0,2],[1,3],[2,5],[3,6],[4,2]]

y = [0,0,0,1,1]

# 实例化API
estimator = KNeighborsClassifier(n_neighbors=3)
estimator.fit(x,y)

#　预测

mypre = estimator.predict([[3,6],[3,4],[2,5])
print(f'mypre:{mypre}')