LinearRegression() 에러입니다^^

안녕하세요. 교수님 너무 좋은 강의 잘 듣고 있습니다.
바쁘실텐데 바로바로 답변해주셔서 너무 감사드려요^^

Bike Sharing Demend 예제소스 에러 질문이 있어서요..
최근에 설치했는데.. 에러가 많이나서

사이킷런 1.0.2 파이썬 3.9.18으로 다운그레이했습니다. 넘파이는 몇버전으로 해야 할까요?

아래는 에러내용입니다.

[ 로그 변환, 피처 인코딩, 모델 학습/예측/평가 ]

from sklearn.model_selection import train_test_split , GridSearchCV

from sklearn.linear_model import LinearRegression , Ridge , Lasso

y_target = bike_df['count']

X_features = bike_df.drop(['count'],axis=1,inplace=False)

X_train, X_test, y_train, y_test = train_test_split(X_features, y_target, test_size=0.3, random_state=0)

lr_reg = LinearRegression()

lr_reg.fit(X_train, y_train)

pred = lr_reg.predict(X_test)

evaluate_regr(y_test ,pred)

에러
---------------------------------------------------------------------------
DTypePromotionError                       Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_19124\3974685920.py in <module>
     11 lr_reg = LinearRegression()
     12 
---> 13 lr_reg.fit(X_train, y_train)
     14 pred = lr_reg.predict(X_test)
     15 

D:\dev03\anaconda\lib\site-packages\sklearn\linear_model\_base.py in fit(self, X, y, sample_weight)
    660         accept_sparse = False if self.positive else ["csr", "csc", "coo"]
    661 
--> 662         X, y = self._validate_data(
    663             X, y, accept_sparse=accept_sparse, y_numeric=True, multi_output=True
    664         )

D:\dev03\anaconda\lib\site-packages\sklearn\base.py in _validate_data(self, X, y, reset, validate_separately, **check_params)
    579                 y = check_array(y, **check_y_params)
    580             else:
--> 581                 X, y = check_X_y(X, y, **check_params)
    582             out = X, y
    583 

D:\dev03\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, estimator)
    962         raise ValueError("y cannot be None")
    963 
--> 964     X = check_array(
    965         X,
    966         accept_sparse=accept_sparse,

D:\dev03\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, estimator)
    663 
    664         if all(isinstance(dtype, np.dtype) for dtype in dtypes_orig):
--> 665             dtype_orig = np.result_type(*dtypes_orig)
    666 
    667     if dtype_numeric:

DTypePromotionError: The DType <class 'numpy.dtypes.