我有一个类名数组：

classes = np.array(['A', 'B'])

我还有一个数据数组（但这些数据只包含一个类别的实例）：

vals = np.array(['A', 'A', 'A'])vals = vals.reshape(len(vals), 1)

我想对vals数组进行独热编码，以便它能考虑到可能存在其他类别。我尝试使用sklearn.preprocessing.OneHotEncoder：

ohe = OneHotEncoder(sparse=False, categories=classes)ohe.fit_transform(vals)

但当我运行这段代码时，我得到了以下错误：

Traceback (most recent call last):  File "/usr/local/anaconda3/envs/my_project/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3331, in run_code    exec(code_obj, self.user_global_ns, self.user_ns)  File "<ipython-input-10-08d325b5e8a7>", line 1, in <module>    ohe.fit_transform(vals)  File "/usr/local/anaconda3/envs/my_project/lib/python3.6/site-packages/sklearn/preprocessing/_encoders.py", line 372, in fit_transform    return super().fit_transform(X, y)  File "/usr/local/anaconda3/envs/my_project/lib/python3.6/site-packages/sklearn/base.py", line 571, in fit_transform    return self.fit(X, **fit_params).transform(X)  File "/usr/local/anaconda3/envs/my_project/lib/python3.6/site-packages/sklearn/preprocessing/_encoders.py", line 347, in fit    self._fit(X, handle_unknown=self.handle_unknown)  File "/usr/local/anaconda3/envs/my_project/lib/python3.6/site-packages/sklearn/preprocessing/_encoders.py", line 76, in _fit    if self.categories != 'auto':ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

回答：

你可以用classes来拟合编码器，然后转换vals：