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我对此感到非常困惑。我正在尝试对数据集执行线性回归，由于我的数据集需要是 2D 而不是 1D，因此我在程序的早期收到了一个值错误，所以我像这样重塑了数据集的每个部分：

x1_train = np.array(x1_train.reshape(-1, 1))
y_train = np.array(y_train.reshape(-1, 1))
x1_test = np.array(x1_test.reshape(-1, 1))
y_test = np.array(y_test.reshape(-1, 1))
x1_pred = np.array(x1_pred.reshape(-1, 1))
y_pred = np.array(y_pred.reshape(-1, 1))

现在，稍后当我尝试绘制训练数据集时，我得到另一个值错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-91-6b2e11318dc3> in <module>
      1 # Visualizing our results
      2 plt.scatter(x1_train, y_train, color = 'green')
----> 3 plt.plot(x1_train, y_pred, color = 'red')
      4 plt.title('Happiness Index Score vs. GDP Per Capita(Training Dataset)')
      5 plt.xlabel('GDP Per Capita')

~\anaconda3\lib\site-packages\matplotlib\pyplot.py in plot(scalex, scaley, data, *args, **kwargs)
   2759 @docstring.copy(Axes.plot)
   2760 def plot(*args, scalex=True, scaley=True, data=None, **kwargs):
-> 2761     return gca().plot(
   2762         *args, scalex=scalex, scaley=scaley, **({"data": data} if data
   2763         is not None else {}), **kwargs)

~\anaconda3\lib\site-packages\matplotlib\axes\_axes.py in plot(self, scalex, scaley, data, *args, **kwargs)
   1645         """
   1646         kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D)
-> 1647         lines = [*self._get_lines(*args, data=data, **kwargs)]
   1648         for line in lines:
   1649             self.add_line(line)

~\anaconda3\lib\site-packages\matplotlib\axes\_base.py in __call__(self, *args, **kwargs)
    214                 this += args[0],
    215                 args = args[1:]
--> 216             yield from self._plot_args(this, kwargs)
    217 
    218     def get_next_color(self):

~\anaconda3\lib\site-packages\matplotlib\axes\_base.py in _plot_args(self, tup, kwargs)
    340 
    341         if x.shape[0] != y.shape[0]:
--> 342             raise ValueError(f"x and y must have same first dimension, but "
    343                              f"have shapes {x.shape} and {y.shape}")
    344         if x.ndim > 2 or y.ndim > 2:

ValueError: x and y must have same first dimension, but have shapes (104, 1) and (52, 1)

这是产生该错误消息/回溯的代码：

plt.scatter(x1_train, y_train, color = 'green')
plt.plot(x1_train, y_pred, color = 'red')
plt.title('Happiness Index Score vs. GDP Per Capita(Training Dataset)')
plt.xlabel('GDP Per Capita')
plt.ylabel('Happiness Index Score')
plt.show()

任何人都明白这里发生了什么？

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