Now that we have formatted our data, we can fit a model using sklearn's Ridge$()$ class. We'll write a function that will take as input the features and response variables that we created in the last question, and returns a trained model.

Function Specifications:

Should take two numpy arrays as input in the form $($X$\_$train, y$\_$train$).$

Should return an sklearn Ridge model.

The returned model should be fitted to the data.

Hint: You may need to reshape the data within the function. You can use to do this.

$]$:

## START FUNCTION

def train$\_$model$($X$\_$train, y$\_$train$)$:

# your code here

return

### END FUNCTION

data $=$ get$\_$year$\_$pop$(\text{'}$Aruba$\text{'})$