线性回归模型给我 keyError 0

Question

我已经为线性回归模型编写了一些代码来预测房价。我的想法与教程视频完全相同；当我写

random_state=42

时，它可以正常工作，没有任何错误，但是当我将

random_state

更改为任何其他数字时，它会出现此错误。

这是代码：

from sklearn.model_selection import train_test_split  
X = data.drop('SalesPrice', axis = 1)
y = data['SalesPrice']
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

from sklearn.linear_model import LinearRegression
lr = LinearRegression()
lr.fit(X_train, y_train)

predictions = lr.predict(X_test)

print("Actual value of the house: ", y_test[0])
print("Model prediction value: ", predictions[0])

这是错误：

KeyError                                  Traceback (most recent call last)
File C:\ProgramData\anaconda3\Lib\site-packages\pandas\core\indexes\base.py:3653, in Index.get_loc(self, key)
   3652 try:
-> 3653     return self._engine.get_loc(casted_key)
   3654 except KeyError as err:

File C:\ProgramData\anaconda3\Lib\site-packages\pandas\_libs\index.pyx:147, in pandas._libs.index.IndexEngine.get_loc()

File C:\ProgramData\anaconda3\Lib\site-packages\pandas\_libs\index.pyx:176, in pandas._libs.index.IndexEngine.get_loc()

File pandas\_libs\hashtable_class_helper.pxi:2606, in pandas._libs.hashtable.Int64HashTable.get_item()

File pandas\_libs\hashtable_class_helper.pxi:2630, in pandas._libs.hashtable.Int64HashTable.get_item()

KeyError: 0

The above exception was the direct cause of the following exception:

KeyError                                  Traceback (most recent call last)
Cell In[66], line 3
      1 predictions = lr.predict(X_test)
----> 3 print("Actual value of the house: ", y_test[0])
      4 print("Model prediction value: ", predictions[0])

File C:\ProgramData\anaconda3\Lib\site-packages\pandas\core\series.py:1007, in Series.__getitem__(self, key)
   1004     return self._values[key]
   1006 elif key_is_scalar:
-> 1007     return self._get_value(key)
   1009 if is_hashable(key):
   1010     # Otherwise index.get_value will raise InvalidIndexError
   1011     try:
   1012         # For labels that don't resolve as scalars like tuples and frozensets

File C:\ProgramData\anaconda3\Lib\site-packages\pandas\core\series.py:1116, in Series._get_value(self, label, takeable)
   1113     return self._values[label]
   1115 # Similar to Index.get_value, but we do not fall back to positional
-> 1116 loc = self.index.get_loc(label)
   1118 if is_integer(loc):
   1119     return self._values[loc]

File C:\ProgramData\anaconda3\Lib\site-packages\pandas\core\indexes\base.py:3655, in Index.get_loc(self, key)
   3653     return self._engine.get_loc(casted_key)
   3654 except KeyError as err:
-> 3655     raise KeyError(key) from err
   3656 except TypeError:
   3657     # If we have a listlike key, _check_indexing_error will raise
   3658     #  InvalidIndexError. Otherwise we fall through and re-raise
   3659     #  the TypeError.
   3660     self._check_indexing_error(key)

KeyError: 0

Answer 1

正如回溯所提到的，错误源自

print("Actual value of the house: ", y_test[0])

。

仅当随机 20% 的数据在

y_test[0]

 之后也有第 

0

 索引时，

train_test_split

才会起作用。这就是为什么它适用于某些

random_state

值，但不适用于大多数值。

通常您想使用：

y_test.to_list()[0]
y_test.iloc[0]

TLDR：替换打印语句中的

y_test[0]