When evaluating a regression mannequin, one of many first metrics you’re prone to encounter is the R² rating, often known as the coefficient of willpower. However what precisely is R²? How can we interpret it? And the way does it relate to different metrics like Imply Squared Error (MSE) or Root Imply Squared Error (RMSE)?
On this article, we’ll break down the R² metric in depth, present hands-on code examples in Python utilizing scikit-learn, and discover its limitations and finest use circumstances.
R² is a statistical measure that represents the proportion of the variance within the dependent variable that’s predictable from the impartial variables.
R² is a relative measure. It doesn’t let you know how good the predictions are, solely how a lot better they’re in comparison with predicting the imply.
