R2 / R-squared

The R-squared metrics aim to give you a sense about accuracy in predictions. It shows how well the model predicts the actual values. R-squared is a measurement of how well the model fits the data.

The closer the value of r-squared is to 0, the bigger the difference between actual value and predicted value.

The closer the R-squared value is to 1, the better predictions.

When to use R-squared

It is important to use R-squared in conjunction with other metrics for your analysis. Treat R-squared as an estimate for your model’s strength, not as a proof of it.