这是x_train
array([[1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1],
[0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0]])
这是y_train：
array([[1, 0, 0, 0, 1, 0],
[0, 1, 0, 1, 0, 0],
[0, 0, 1, 0, 0, 1]])
使用的逻辑回归：
from sklearn.linear_model import LogisticRegression
lr=LogisticRegression()
lr.fit(x_train,y_train)
错误：
/opt/conda/lib/python3.7/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)
758 dtype=None)
759 else:
--> 760 y = column_or_1d(y, warn=True)
761 _assert_all_finite(y)
762 if y_numeric and y.dtype.kind == 'O':
/opt/conda/lib/python3.7/site-packages/sklearn/utils/validation.py in column_or_1d(y, warn)
795 return np.ravel(y)
796
--> 797 raise ValueError("bad input shape {0}".format(shape))
798
799
ValueError: bad input shape (3, 6)
我们该如何解决？ 谢谢