训练linear_model时报错TypeError: invalid type promotion

from sklearn.linear_model import LinearRegression
linear_model = LinearRegression()
linear_model = linear_model.fit(X_train, y_train)

这是报错

TypeError                                 Traceback (most recent call last)
<ipython-input-45-bb85c21c334c> in <module>
      1 from sklearn.linear_model import LinearRegression
      2 linear_model = LinearRegression()
----> 3 linear_model = linear_model.fit(X_train, y_train)

D:\anaconda\lib\site-packages\sklearn\linear_model\_base.py in fit(self, X, y, sample_weight)
    490         n_jobs_ = self.n_jobs
    491         X, y = check_X_y(X, y, accept_sparse=['csr', 'csc', 'coo'],
--> 492                          y_numeric=True, multi_output=True)
    493 
    494         if sample_weight is not None:

D:\anaconda\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, warn_on_dtype, estimator)
    753                     ensure_min_features=ensure_min_features,
    754                     warn_on_dtype=warn_on_dtype,
--> 755                     estimator=estimator)
    756     if multi_output:
    757         y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False,

D:\anaconda\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, warn_on_dtype, estimator)
    473 
    474         if all(isinstance(dtype, np.dtype) for dtype in dtypes_orig):
--> 475             dtype_orig = np.result_type(*dtypes_orig)
    476 
    477     if dtype_numeric:

<__array_function__ internals> in result_type(*args, **kwargs)

TypeError: invalid type promotion

图片是X_train和y_train的输出，不知道是不是格式有误啊，为什么LInearModel训练不了呢

请问解决了吗

https://blog.csdn.net/wj1298250240/article/details/103251007