Question

我正在努力完成Sebastian Raschka关于功能扩展的教程，我无法获得下面的代码来运行，因为它会抛出第三行的错误，结果是＆＃39; python＆＃39 ;.

from matplotlib import pyplot as plt

fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2, figsize=(10,5))

y_p    :::python
    # Standardization

    x = [1,4,5,6,6,2,3]
    mean = sum(x)/len(x)
    std_dev = (1/len(x) * sum([ (x_i - mean)**2 for x_i in x]))**0.5

    z_scores = [(x_i - mean)/std_dev for x_i in x]

    # Min-Max scaling

    minmax = [(x_i - min(x)) / (min(x) - max(x)) for x_i in x]os = [0 for i in range(len(x))]

ax1.scatter(z_scores, y_pos, color='g')
ax1.set_title('Python standardization', color='g')

ax2.scatter(minmax, y_pos, color='g')
ax2.set_title('Python Min-Max scaling', color='g')

ax3.scatter(z_scores_np, y_pos, color='b')
ax3.set_title('Python NumPy standardization', color='b')
The-effect-of-standardization
ax4.scatter(np_minmax, y_pos, color='b')
ax4.set_title('Python NumPy Min-Max scaling', color='b')

plt.tight_layout()

for ax in (ax1, ax2, ax3, ax4):
    ax.get_yaxis().set_visible(False)
    ax.grid()

plt.show()

那么，y_p ::: python做什么？

Answer 1

答案是它不是有效的python代码。

你应该看一下ipython笔记本，我相信你从中获得了代码的某些部分。

http://nbviewer.jupyter.org/github/rasbt/pattern_classification/blob/master/preprocessing/about_standardization_normalization.ipynb

y_p ::: python在这个（或任何）脚本中做了什么？

1 个答案: