The R^2 value in scikit learn is the same on the coefficient of determination. It is a 1-residual sum of square / total sum of squares.

The big difference between a classical stats setting and machine learning is that you evaluate your score on unseen data, which can lead to results outside [0,1]. If you apply R^2 to the same data you used to fit your model, it will lie within [0, 1]

Hope this answer helps you!