%%time
best_method = ""
best_p = -1
best_score = 0.0
best_k = -1

for method in ["uniform","distance"]:
    for k in range(1,10):
        for p in range(1,6):
            knn_clf = KNeighborsClassifier(n_neighbors = k,weights = method,p=p)
            knn_clf.fit(X_train,y_train)
            score = knn_clf.score(X_test,y_test)
            if score > best_score:
                best_k = k
                best_method = method
                best_p = p
                best_score = score
                
print("best_score = ",best_method)
print("best_p = ",best_p)
print("best_score = ",best_score)
print("best_k = ",best_k)

best_score =  uniform
best_p =  2
best_score =  0.9916666666666667
best_k =  4
Wall time: 36.7 s

best_score =  distance
best_p =  2
best_score =  0.9888888888888889
best_k =  3
Wall time: 17.4 s

既然p是在weight为distance时才有存在的意义

那2这个结果的理解是不是可以看出，相对而言，选择对的weight比选择对的p更加重要，weight更加超呢？？