使用 python 中嵌套 for 循環中的不同變量創建數組或 dataframe

Question

如何創建一個數組或 dataframe 來存儲 seedN, clf.score(X_test, y_test) , n_neighbors ？

from sklearn.model_selection import train_test_split

for seedN in range(1,50,1):
    X_train, X_test, y_train, y_test = train_test_split(indicators,data2['target'], 
                                                        test_size=0.25, random_state=seedN)

    training_accuracy = []
    test_accuracy = []
    
    neighbors_settings = range(1, 70) # try n_neighbors from 1 to 50

    for n_neighbors in neighbors_settings:   
        clf = KNeighborsClassifier(n_neighbors=n_neighbors)  # build the model
        clf.fit(X_train, y_train)
        training_accuracy.append(clf.score(X_train, y_train)) # record training set accuracy
        test_accuracy.append(clf.score(X_test, y_test))   # record generalization accuracy

Answer 1

創建一個臨時空列表來存儲結果：

tmp = []

對於每個擬合，添加一個包含所需值的新列表：

for seedN in range(1, 50, 1):
    # your code
    for n_neighbors in neighbors_settings:
        # your code
        tmp.append([seedN, clf.score(X_test, y_test), n_neighbors]) 

最后，使用這個臨時列表創建 dataframe：

df = pd.DataFrame(tmp, columns=["seedN", "score", "n_neighbors"])