Traceback (most recent call last): File "D:/pythonProject/find_k.py", line 11, in <module> x_train,x_test,y_train,y_test=train_test_split(data.iloc[:,1:],data.iloc[:,0],test_size=0.2,stratify=data.iloc[:,0]) File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_split.py", line 2441, in train_test_split train, test = next(cv.split(X=arrays[0], y=stratify)) File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_split.py", line 1600, in split for train, test in self._iter_indices(X, y, groups): File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_split.py", line 1941, in _iter_indices "The least populated class in y has only 1" ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.

这个错误是由于在使用`train_test_split`函数时，数据集中某个类别的样本数量过少导致的。`train_test_split`函数默认会根据`stratify`参数进行分层抽样，确保训练集和测试集中各类别样本的比例相同。但是，如果某个类别的样本数量只有1个，那么无法满足分层抽样的要求。

解决这个问题的方法是检查数据集中各类别的样本数量，确保每个类别至少有2个样本。可以考虑增加数据集中该类别的样本数量，或者使用其他的分割方法来避免这个问题。