ظهور الخطأ التالي ValueError: Found array with dim 3. Estimator expected <= 2 عند محاولة تدريب نموذج

ظهور الخطأ التالي ValueError: Found array with dim 3. Estimator expected <= 2 عند محاولة تدريب نموذج باستخدام خوارزمية  MultinomialNB؟

import numpy as np
from tensorflow.keras.datasets import mnist
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline
from tensorflow.keras.utils import to_categorical
from sklearn.metrics import f1_score,precision_score,recall_score,accuracy_score,log_loss
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train.shape
t = Pipeline([('clf',MultinomialNB())])
t = text_clf.fit(x_train, y_train)
accuracy_score(y_test,t.predict(x_test))
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-25-434bf8f46433> in <module>
     10 # تعريف pipline
     11 t = Pipeline([('clf',MultinomialNB())])
---> 12 t = text_clf.fit(x_train, y_train)
     13 accuracy_score(y_test,t.predict(x_test))

~\anaconda3\lib\site-packages\sklearn\pipeline.py in fit(self, X, y, **fit_params)
    352                                  self._log_message(len(self.steps) - 1)):
    353             if self._final_estimator != 'passthrough':
--> 354                 self._final_estimator.fit(Xt, y, **fit_params)
    355         return self
    356 

~\anaconda3\lib\site-packages\sklearn\naive_bayes.py in fit(self, X, y, sample_weight)
    607         self : object
    608         """
--> 609         X, y = self._check_X_y(X, y)
    610         _, n_features = X.shape
    611         self.n_features_ = n_features

~\anaconda3\lib\site-packages\sklearn\naive_bayes.py in _check_X_y(self, X, y)
    473 
    474     def _check_X_y(self, X, y):
--> 475         return check_X_y(X, y, accept_sparse='csr')
    476 
    477     def _update_class_log_prior(self, class_prior=None):

~\anaconda3\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,

~\anaconda3\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)
    572         if not allow_nd and array.ndim >= 3:
    573             raise ValueError("Found array with dim %d. %s expected <= 2."
--> 574                              % (array.ndim, estimator_name))
    575 
    576         if force_all_finite:

ValueError: Found array with dim 3. Estimator expected <= 2.