Python knn输入与网格搜索相结合

我试图从数据帧中插补缺失值，为此，我使用knn插补器。我想结合knn输入和网格搜索，但我不知道如何做到这一点。我试试这个代码

alphas_knn_imputer =list(range(10,40,1))
params_knn_imputer={'KNNImputer__n_neighbors':alphas_knn_imputer}
knn_imputer =GridSearchCV(KNNImputer(),params_knn_imputer,cv=4)

num_proc_knn = make_pipeline(
    knn_imputer,
    StandardScaler()
)

processor_col_inknn = make_column_transformer(
    (num_proc_knn, num_cols),
    remainder='passthrough')
    
   
lineare_reg_knn = make_pipeline(processor_col_inknn,LinearRegression())
lineare_reg_knn.fit(X_train,Y_train)
lineare_reg_knn.score(X_test,Y_test)   

我有一个错误：

If no scoring is specified, the estimator passed should have a 'score' method. The estimator KNNImputer(add_indicator=False, copy=True, metric='nan_euclidean',
           missing_values=nan, n_neighbors=5, weights='uniform') does not.