How to interpret R^2 value in a regression model?

Question

I computed the R² (R-squared) value using the output of a regression model, which is 0.8. How to interpret R² value? Is it a good value?

Answer 1

In any regression model, the R² (R-squared) value is a key performance metric, and the bigger the R² value, the better the prediction.

Here's how to interpret the R² value:

R² = 1 -> Perfect prediction. The model explains all the variability of the target variable.
R² = 0 -> The model does no better than simply predicting the mean of the target.
R² < 0 -> The model is worse than using the mean as a prediction.

So, your value of 0.8 is close to a good prediction.