AttributeError: 'DataFrame' object has no attribute 'mean_squared_error'

This error occurs because you are trying to call the `mean_squared_error` function on a DataFrame object, which does not have this attribute.

`mean_squared_error` is a function from the `sklearn.metrics` module. To use it, you need to import it and call it with two arrays or series of actual and predicted values. Here's an example:

from sklearn.metrics import mean_squared_error
import pandas as pd

# create two series of actual and predicted values
actual = pd.Series([1, 2, 3])
predicted = pd.Series([1.5, 2.5, 3.5])

# calculate mean squared error
mse = mean_squared_error(actual, predicted)
print(mse)

In this example, we first import the `mean_squared_error` function from `sklearn.metrics`. Then we create two series of actual and predicted values. Finally, we call `mean_squared_error` with these two series to calculate the mean squared error between them.