在训练情感分析模型时如何修复 ValueError？

Question

我正在尝试为情绪分析训练逻辑回归模型。 尝试标准化功能和尝试训练模型时出现以下错误：

我在这里发布了完整的追溯

ValueError                                Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_18368/1468496602.py in <module>
----> 1 model = logistic_regression.fit(features, target)

~\anaconda3\anacondadownload\lib\site-packages\sklearn\linear_model\_logistic.py in fit(self, X, y, sample_weight)
   1342             _dtype = [np.float64, np.float32]
   1343 
-> 1344         X, y = self._validate_data(X, y, accept_sparse='csr', dtype=_dtype,
   1345                                    order="C",
   1346                                    accept_large_sparse=solver != 'liblinear')

~\anaconda3\anacondadownload\lib\site-packages\sklearn\base.py in _validate_data(self, X, y, reset, validate_separately, **check_params)
    431                 y = check_array(y, **check_y_params)
    432             else:
--> 433                 X, y = check_X_y(X, y, **check_params)
    434             out = X, y
    435 

~\anaconda3\anacondadownload\lib\site-packages\sklearn\utils\validation.py in inner_f(*args, **kwargs)
     61             extra_args = len(args) - len(all_args)
     62             if extra_args <= 0:
---> 63                 return f(*args, **kwargs)
     64 
     65             # extra_args > 0

~\anaconda3\anacondadownload\lib\site-packages\sklearn\utils\validation.py in check_X_y(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)
    869         raise ValueError("y cannot be None")
    870 
--> 871     X = check_array(X, accept_sparse=accept_sparse,
    872                     accept_large_sparse=accept_large_sparse,
    873                     dtype=dtype, order=order, copy=copy,

~\anaconda3\anacondadownload\lib\site-packages\sklearn\utils\validation.py in inner_f(*args, **kwargs)
     61             extra_args = len(args) - len(all_args)
     62             if extra_args <= 0:
---> 63                 return f(*args, **kwargs)
     64 
     65             # extra_args > 0

~\anaconda3\anacondadownload\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)
    671                     array = array.astype(dtype, casting="unsafe", copy=False)
    672                 else:
--> 673                     array = np.asarray(array, order=order, dtype=dtype)
    674             except ComplexWarning as complex_warning:
    675                 raise ValueError("Complex data not supported\n"

~\anaconda3\anacondadownload\lib\site-packages\numpy\core\_asarray.py in asarray(a, dtype, order, like)
    100         return _asarray_with_like(a, dtype=dtype, order=order, like=like)
    101 
--> 102     return array(a, dtype, copy=False, order=order)
    103 
    104 

~\anaconda3\anacondadownload\lib\site-packages\pandas\core\series.py in __array__(self, dtype)
    855               dtype='datetime64[ns]')
    856         """
--> 857         return np.asarray(self._values, dtype)
    858 
    859     # ----------------------------------------------------------------------

~\anaconda3\anacondadownload\lib\site-packages\numpy\core\_asarray.py in asarray(a, dtype, order, like)
    100         return _asarray_with_like(a, dtype=dtype, order=order, like=like)
    101 
--> 102     return array(a, dtype, copy=False, order=order)
    103 
    104 

ValueError: could not convert string to float: 'clint eastwood return dirti harri calahan movi dirti harri seri clint older he still got harri told vacat troubl happen robberi memor make day catchphras come citi took vacat wors woman turn vigilant rape attack funfair start get punk one one last movi see sandra lock clint eastwood movi improv enforc bit comedi less seriou clint eastwood sunglass gargoyl best known sunglass worn arnold shwartzeneg termin worth watch like clint eastwood dirti harri film like action crime thriller'

​

如果需要从数据中删除，我不确定如何解决这个问题？ 我已经对此进行了一些文本处理，例如删除停用词、小写字母、删除标点符号。

我没有将任何值转换为浮点数

Answer 1

请问您将字符串转换为浮点数是为了什么？ float()的用法可以参考文档。

据我所知，他们在情感分析中使用 word2vec 将句子转换为数字序列，而不是 float()。 如果您可以支持更多信息，那就太好了。