[英]too many values to unpack (expected 2)?
我有要使用的數據框,當我測試/拆分數據時會彈出此錯誤消息
太多值無法解包(預期2)
我只是將train_test_split的目標列Global設置為y值,其余列設置為X。 不確定從哪里開始解決此問題
X = df[['Year_of_Release', 'Critic_Score', 'Critic_Count',
'User_Score', 'User_Count', 'Platform_PC', 'Platform_PS3',
'Platform_PS4', 'Platform_Wii', 'Platform_X360',
'Platform_XOne', 'Genre_Action', 'Genre_Adventure', 'Genre_Fighting',
'Genre_Misc', 'Genre_Platform', 'Genre_Puzzle', 'Genre_Racing',
'Genre_Role-Playing', 'Genre_Shooter', 'Genre_Simulation',
'Genre_Sports', 'Genre_Strategy', 'Rating_E', 'Rating_E10+', 'Rating_M',
'Rating_RP', 'Rating_T']]
y = df[['Global']]
print(X.shape)
print(y.shape)
from sklearn.model_selection import train_test_split
X_train, X_test = train_test_split(X, y, train_size=0.8, test_size=0.2, random_state=42)
X_train, X_val = train_test_split(X_train, train_size=0.8, test_size=0.2, random_state=42)
target = 'Global'
y_train = X_train[target]
y_val = X_val[target]
y_test = X_test[target]
X_train = X_train.drop(columns=target)
X_val = X_val.drop(columns=target)
X_test = X_test.drop(columns=target)
X_train.shape, y_train.shape, X_val.shape, y_val.shape, X_test.shape, y_test.shape
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-75-d3fede999d7b> in <module>()
1 from sklearn.model_selection import train_test_split
2
----> 3 X_train, X_test = train_test_split(X, y, train_size=0.8, test_size=0.2, random_state=42)
4
5
ValueError: too many values to unpack (expected 2)
sklearn的train_test_split返回4個值X_Train和y_train以及X_test y_test。 請參閱此處的官方文檔。
另外,您應指定測試尺寸或火車尺寸 。
X = df[['Year_of_Release', 'Critic_Score', 'Critic_Count',
'User_Score', 'User_Count', 'Platform_PC', 'Platform_PS3',
'Platform_PS4', 'Platform_Wii', 'Platform_X360',
'Platform_XOne', 'Genre_Action', 'Genre_Adventure', 'Genre_Fighting',
'Genre_Misc', 'Genre_Platform', 'Genre_Puzzle', 'Genre_Racing',
'Genre_Role-Playing', 'Genre_Shooter', 'Genre_Simulation',
'Genre_Sports', 'Genre_Strategy', 'Rating_E', 'Rating_E10+', 'Rating_M',
'Rating_RP', 'Rating_T']]
y = df[['Global']]
print(X.shape)
print(y.shape)
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
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