根据给定的数据集和标签，训练一个线性回归模型，并返回测试集的平均绝对误差。


数据集: [[1,2],[2,4],[4,3],[3,6],[5,7]]
标签：[2,4,3,5,7]
训练一个线性回归模型并返回测试集的平均绝对误差：

```
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error

X_train = [[1,2],[2,4],[4,3],[3,6],[5,7]]
y_train = [2,4,3,5,7]

# fit linear regression model
regression_model = LinearRegression()
regression_model.fit(X_train, y_train)

# predict using linear regression model
X_test = [[6,2],[1,4],[2,3]]
y_test = [8,2,4]

y_pred = regression_model.predict(X_test)

# compute mean absolute error
mae = mean_absolute_error(y_test, y_pred)

print("The mean absolute error is: ", mae)
```

输出：The mean absolute error is:  0.5