如何修复分类数据集 MNIST 中的以下错误：-

Question

我将 mnist 指定为：

mnist = fetch_openml('mnist_784', version = 1)

在探索 MNIST 数据集时，分配后：

X, y = mnist["data"], mnist["target"]

我试图抓取一个实例的特征向量，将其重塑为 28×28 数组，在此之前我分配了：

some_digit = X[0]

我收到错误：

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
c:\users\kanishk\appdata\local\programs\python\python39\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   3079             try:
-> 3080                 return self._engine.get_loc(casted_key)
   3081             except KeyError as err:

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 0

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

KeyError                                  Traceback (most recent call last)
<ipython-input-8-348a6e96ae02> in <module>
----> 1 some_digit = X[0]

c:\users\kanishk\appdata\local\programs\python\python39\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   3022             if self.columns.nlevels > 1:
   3023                 return self._getitem_multilevel(key)
-> 3024             indexer = self.columns.get_loc(key)
   3025             if is_integer(indexer):
   3026                 indexer = [indexer]

c:\users\kanishk\appdata\local\programs\python\python39\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   3080                 return self._engine.get_loc(casted_key)
   3081             except KeyError as err:
-> 3082                 raise KeyError(key) from err
   3083 
   3084         if tolerance is not None:

KeyError: 0

我该如何解决？

Answer 1

您的 X 似乎是 pandas.DataFrame，在 DataFrame 代码中 X[0] 搜索名称为 0 的列，但 X 没有有了。

如果你想获得编号为 0 的行，那么你可能需要 X.iloc[0]

顺便说一句：

当我运行

from sklearn.datasets import fetch_openml

mnist = fetch_openml('mnist_784', version=1)

X, y = mnist["data"], mnist["target"]
print(type(X), X.shape)  # <class 'numpy.ndarray'> (70000, 784)

some_digit = X[0]
print(type(some_digit), some_digit.shape)  # <class 'numpy.ndarray'> (784,)

然后我得到 X 因为 numpy.array 和 X[0] 给了我期望值。

也许您在某个地方将 X 从 numpy.array 转换为 pandas.DataFrame - 现在您必须使用不同的方法来访问数据。

如何修复分类数据集 MNIST 中的以下错误：-

How to fix the following error in Classification dataset MNIST :-

python

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