ValueError: Cannot have number of splits n_splits=3 greater than the number of samples: 1

Question

我正在尝试使用 train_test_split 和决策树回归器进行训练建模：

import sklearn
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeRegressor
from sklearn.model_selection import cross_val_score

# TODO: Make a copy of the DataFrame, using the 'drop' function to drop the given feature
new_data = samples.drop('Fresh', 1)

# TODO: Split the data into training and testing sets using the given feature as the target
X_train, X_test, y_train, y_test = train_test_split(new_data, samples['Fresh'], test_size=0.25, random_state=0)

# TODO: Create a decision tree regressor and fit it to the training set
regressor = DecisionTreeRegressor(random_state=0)
regressor = regressor.fit(X_train, y_train)

# TODO: Report the score of the prediction using the testing set
score = cross_val_score(regressor, X_test, y_test, cv=3)

print score

当运行这个时，我收到错误：

ValueError: Cannot have number of splits n_splits=3 greater than the number of samples: 1.

如果我将 cv 的值更改为 1，我得到：

ValueError: k-fold cross-validation requires at least one train/test split by setting n_splits=2 or more, got n_splits=1.

一些示例数据行如下所示：

    Fresh   Milk    Grocery Frozen  Detergents_Paper    Delicatessen
0   14755   899 1382    1765    56  749
1   1838    6380    2824    1218    1216    295
2   22096   3575    7041    11422   343 2564

Answer 1

如果分割数大于样本数，你会得到第一个错误。检查下面给出的 source code 中的代码段：

if self.n_splits > n_samples:
    raise ValueError(
        ("Cannot have number of splits n_splits={0} greater"
         " than the number of samples: {1}.").format(self.n_splits,
                                                     n_samples))

如果折叠数小于或等于1，你会得到第二个错误。在你的例子中，cv = 1。检查 source code:

if n_folds <= 1:
            raise ValueError(
                "k-fold cross validation requires at least one"
                " train / test split by setting n_folds=2 or more,"
                " got n_folds={0}.".format(n_folds))

有根据的猜测，X_test中的样本数量少于3。仔细检查。

ValueError: Cannot have number of splits n_splits=3 greater than the number of samples: 1

ValueError: Cannot have number of splits n_splits=3 greater than the number of samples: 1

python

scikit-learn

cross-validation

sklearn-pandas