scikit-learn - “分割数 n_splits=3 不能大于样本数：n

我正在尝试使用 k 折交叉验证来比较我的多项式回归和支持向量机模型。（x 轴 = 油耗，y 轴 = 距离）

以下是我一直在尝试但出现错误的代码

"ValueError: cannot have number of splits n_splits=3 greater than the number of samples: n_samples=1"

代码：

from sklearn.model_selection import KFold
kf = Fold(n_splits=3)
kf

x=data.iloc[:,0]
y=data.iloc[:,1]

from sklearn.model_selection import train_test_split
x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.3)

for train_index,test_index in kf.split([['Distance']]):
print(train_index,test_index)

样本数据（数据集是二维的）：

Fuel Consumption   Distance
13.046653          444.699427
14.717947          468.604994
15.032536          464.386458

谢谢！

标签： scikit-learnsvm

scikit-learn - “分割数 n_splits=3 不能大于样本数：n_samples=1”