from sklearn.preprocessing import binarize y_pred_class = binarize(y_pred_prob, 0.3)[0] This is the warning error; "C:\Users\THINK\.conda\envs\tens\lib\site-packages\sklearn\utils\validation.py:70: FutureWarning: Pass threshold=0.3 as keyword args. From version 0.25 passing these as positional arguments will result in an error FutureWarning)" Error ; "conda\envs\tens\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) 621 "Reshape your data either […]

- Tags -1) " --> 623 "if it contains a single sample.".format(array)) 624 625 # in the future np.flexible dtype, -1) if it contains a single sample., 'copy', 'dtype':, $order, 0.3)[0] This is the warning error; "C:\Users\THINK\.conda\envs\tens\lib\site-packages\sklearn\utils\validation.py:70: FutureWarning: Pass, 1) if " 622 "your data has a single feature or array.reshape(1, 1) if your data has a single feature or array.reshape(1, accept_large_sparse, accept_sparse, allow_nd, ensure_2d, ensure_min_features, ensure_min_samples, estimator) 621 "Reshape your data either using array.reshape(-1, force_all_finite, from sklearn.preprocessing import binarize y_pred_class = binarize(y_pred_prob, got 1D array instead:" "Reshape your data either using array.reshape(-1