为什么在 MNIST 分类器代码中使用 X[0] 会给我一个错误？

Question

我正在学习使用 MNIST 数据集进行分类。我遇到了一个我无法弄清楚的错误，我已经做了很多谷歌搜索，但我无能为力，也许你是专家并且可以帮助我。这是代码--

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

输出： dict_keys(['数据', '目标', '框架', '类别', 'feature_names', 'target_names', 'DESCR', '详细信息', 'url'])

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

输出:(70000, 784)

>>> y.shape

产量：(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

Answer 1

fetch_openml

的API在版本之间发生了变化。在早期版本中，它返回一个

numpy.ndarray

数组。自

0.24.0

（2020 年 12 月）以来，

as_frame

的

fetch_openml

参数设置为

auto

（而不是之前作为默认选项的

False

），这为您提供了 MNIST 数据的

pandas.DataFrame

。您可以通过设置

numpy.ndarray

强制将数据读取为

as_frame = False

。请参阅 fetch_openml 参考 .

Answer 2

我也面临同样的问题。

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

我曾经使用下面的代码来解决该问题。

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()

Answer 3

如果您按照以下代码操作，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()

Answer 4

您将数据集作为数据框加载，以便能够访问图像，有两种方法可以做到这一点，

将数据帧转换为数组

# Transform the dataframe into an array. Check the first value
some_digit = X.to_numpy()[0]

# Reshape it to (28,28). Note: 28 x 28 = 7064, if the reshaping doesn't meet 
# this you are not able to show the image
some_digit_image = some_digit.reshape(28,28)

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

变换行

# Transform the row of your choosing into an array
some_digit = X.iloc[0,:].values

# Reshape it to (28,28). Note: 28 x 28 = 7064, if the reshaping doesn't 
# meet this you are not able to show the image
some_digit_image = some_digit.reshape(28,28)

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

Answer 5

您可以在加载 mnist 数据集时添加

parser = 'auto'

作为额外参数。

我是这样导入的：

mnist = fetch_openml('mnist_784', version= 1, as_frame= False, parser='auto')