我试图使用Scikit-learn进行随机森林回归。加载数据后使用Pandas的第一步是将数据分成测试集和训练集。然而，我得到了以下错误：

y中最少的类别只有1个成员

我在谷歌上搜索了这个错误，发现了各种实例，但我仍然无法理解这个错误的含义。

training_file = "training_data.txt"data = pd.read_csv(training_file, sep='\t')y = data.ResultX = data.drop('Result', axis=1)X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=123, stratify=y)pipeline = make_pipeline(preprocessing.StandardScaler(), RandomForestRegressor(n_estimators=100))hyperparameters = { 'randomforestregressor__max_features' : ['auto', 'sqrt', 'log2'],                'randomforestregressor__max_depth' : [None, 5, 3, 1] }model = GridSearchCV(pipeline, hyperparameters, cv=10)model.fit(X_train, y_train)prediction = model.predict(X_test)joblib.dump(model, 'ms5000.pkl')

train_test_split方法产生了以下堆栈跟踪：

Traceback (most recent call last):    File "/Users/justin.shapiro/Desktop/IPML_Model/model_definition.py", line 18, in <module>    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.22, random_state=123, stratify=y)  File "/Library/Python/2.7/site-packages/sklearn/model_selection/_split.py", line 1700, in train_test_splittrain, test = next(cv.split(X=arrays[0], y=stratify))  File "/Library/Python/2.7/site-packages/sklearn/model_selection/_split.py", line 953, in splitfor train, test in self._iter_indices(X, y, groups):  File "/Library/Python/2.7/site-packages/sklearn/model_selection/_split.py", line 1259, in _iter_indicesraise ValueError("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.

这是我的数据集的一个样本：

var1    var2    var3    var4    var5    var6    var7    var8    Resulthigh    5000.0  0       60      1000    75      0.23    0.75    17912.0mid     5000.0  0       60      1000    50      0.23    0.75    18707.0low     5000.0  0       60      1000    25      0.23    0.75    17912.0high    5000.0  5       60      1000    75      0.23    0.75    18577.0mid     5000.0  5       60      1000    50      0.23    0.75    19407.0low     5000.0  5       60      1000    25      0.23    0.75    18577.0

这个错误是什么意思，我如何解决它？

回答：

错误发生在这一行：

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.22, random_state=123, stratify=y)

尝试删除stratify=y