为什么在 MNIST 分类器代码中使用 X[0] 会报错?

Why does using X[0] in MNIST classifier code give me an error?

我正在学习使用 MNIST 数据集进行分类。我遇到了一个错误,我无法弄清楚,我已经进行了很多 google 搜索,但我无能为力,也许您是专家可以帮助我。这是代码--

>>> from sklearn.datasets import fetch_openml
>>> mnist = fetch_openml('mnist_784', version=1)
>>> mnist.keys()

输出: dict_keys(['data', 'target', 'frame', 'categories', 'feature_names', 'target_names', 'DESCR', 'details', 'url'])

>>> X, y = mnist["data"], mnist["target"]
>>> X.shape

输出:(70000, 784)

>>> y.shape

输出:(70000)

>>> X[0]

output:KeyError                                  Traceback (most recent call last)
c:\users\khush\appdata\local\programs\python\python39\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2897             try:
-> 2898                 return self._engine.get_loc(casted_key)
   2899             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-10-19c40ecbd036> in <module>
----> 1 X[0]

c:\users\khush\appdata\local\programs\python\python39\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   2904             if self.columns.nlevels > 1:
   2905                 return self._getitem_multilevel(key)
-> 2906             indexer = self.columns.get_loc(key)
   2907             if is_integer(indexer):
   2908                 indexer = [indexer]

c:\users\khush\appdata\local\programs\python\python39\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2898                 return self._engine.get_loc(casted_key)
   2899             except KeyError as err:
-> 2900                 raise KeyError(key) from err
   2901 
   2902         if tolerance is not None:

KeyError: 0

请回答,可能会有一个愚蠢的错误,因为我是 ML 的初学者。如果您也给我一些提示,那将非常有帮助。

fetch_openml 的 API 版本之间发生了变化。在早期版本中,它是 returns 一个 numpy.ndarray 数组。自 0.24.0(2020 年 12 月)起,fetch_openmlas_frame 参数设置为 auto(而不是之前的默认选项 False),这为您提供了 pandas.DataFrame 用于 MNIST 数据。您可以通过设置 as_frame = False 强制将数据读取为 numpy.ndarray。参见 fetch_openml reference

我也遇到了同样的问题

  • scikit-学习:0.24.0
  • matplotlib: 3.3.3
  • Python: 3.9.1

我以前用下面的代码来解决这个问题。

import matplotlib as mpl
import matplotlib.pyplot as plt


# instead of some_digit = X[0]
some_digit = X.to_numpy()[0]
some_digit_image = some_digit.reshape(28,28)

plt.imshow(some_digit_image,cmap="binary")
plt.axis("off")
plt.show()

如果您遵循以下代码,则无需降级 scikit-learn 库:

from sklearn.datasets import fetch_openml
mnist = fetch_openml('mnist_784', version= 1, as_frame= False)
mnist.keys()