Python 通过pickle dump进行预测-ValueError:无法将字符串转换为浮点：

我试图通过通过csv传递一个不可见数据的转储，通过pickled dump获得预测值。 我收到以下错误，无法继续。感谢任何快速解决方法

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ValueError                                Traceback (most recent call last)
<ipython-input-19-c7877b0e4ecc> in <module>
     40     X_test = df_a1['ML_Description'].astype(str)
     41     y_test = df_a1['Classification'].astype(str)
---> 42     ODP_pred_gs_cv = ODP_Model.predict(X_test)
     43     df_a1['Classification'] = ODP_pred_gs_cv
     44     df_a1.to_csv('TOC_IP_ODP_ML_New_Validation_Results.csv',columns=header, index=True)

C:\Programs\Miniconda3_x64\envs\jup369\lib\site-packages\sklearn\linear_model\base.py in predict(self, X)
    287             Predicted class label per sample.
    288         """
--> 289         scores = self.decision_function(X)
    290         if len(scores.shape) == 1:
    291             indices = (scores > 0).astype(np.int)

C:\Programs\Miniconda3_x64\envs\jup369\lib\site-packages\sklearn\linear_model\base.py in decision_function(self, X)
    263                                  "yet" % {'name': type(self).__name__})
    264 
--> 265         X = check_array(X, accept_sparse='csr')
    266 
    267         n_features = self.coef_.shape[1]

C:\Programs\Miniconda3_x64\envs\jup369\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)
    494             try:
    495                 warnings.simplefilter('error', ComplexWarning)
--> 496                 array = np.asarray(array, dtype=dtype, order=order)
    497             except ComplexWarning:
    498                 raise ValueError("Complex data not supported\n"

C:\Programs\Miniconda3_x64\envs\jup369\lib\site-packages\numpy\core\_asarray.py in asarray(a, dtype, order)
     83 
     84     """
---> 85     return array(a, dtype, copy=False, order=order)
     86 
     87 

ValueError: could not convert string to float: 'PrimaryAccountRESManagementTOCI&PCrossFunctionTOC&Infra&PlatformGroupTechnologyADRG232381ADRGA3VDIWorkspaceREADONLYADSamuraiA3VDIWorkspaceREADONLYapp_Global_pooledvdi_vOmega_itaw_userapp_Global_pooledvdi_vOmega_itaw_userADSamuraiARPA3vO'

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通常情况下，机器学习模型无法使用字符串，但您已将功能和输出转换为字符串

X_test = df_a1['ML_Description'].astype(str)
y_test = df_a1['Classification'].astype(str)

X_test = df_a1['ML_Description'].astype(str)
y_test = df_a1['Classification'].astype(str)