Scikit-learn：“ y中人口最少的类只有1个成员”

Question

我正在尝试使用Scikit学习进行随机森林回归。使用Pandas加载数据后的第一步是将数据分为测试集和训练集。但是，我得到了错误：

y中人口最少的阶层只有1个成员

我已经搜索过Google并发现了该错误的各种实例，但是我似乎仍然无法理解该错误的含义。

training_file = "training_data.txt"
data = pd.read_csv(training_file, sep='\t')

y = data.Result
X = 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')

该train_test_split方法产生以下堆栈跟踪：

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_split
train, test = next(cv.split(X=arrays[0], y=stratify))
  File "/Library/Python/2.7/site-packages/sklearn/model_selection/_split.py", line 953, in split
for 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_indices
raise 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示例：

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

这是什么错误，我该如何解决？

Answer 1

此行引发错误：

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