模型引入
from sklearn.neighbors import KNeighborsRegressor
实例化对象
knn_reg=KNeighborsRegressor()
训练数据集
knn_reg.fit(X_train,y_train)
查看评估的成绩
knn_reg.score(X_test,y_test)
运行结果
网格搜索参数:
from sklearn.model_selection import GridSearchCV
param_grid=[
{
'weights':['uniform'],
'n_neighbors':[i for i in range(1,11)]
},
{
'weights':['distance'],
'n_neighbors':[i for i in range(1,11)],
'p':[i for i in range(1,6)]
}
]
knn_reg2=KNeighborsRegressor()
grid_search=GridSearchCV(knn_reg2,param_grid,n_jobs=-1