Adjusted R-squared Value
Adjusted R-squared value is the modification of R-squared Value. In R-squared Value value, it always increases with adding a parameter in the Linear Regression. But it doesn't always mean that it has added a lot of value to the prediction. On the other hand, adjusted R-squared value increases only when the parameter is significant.
Adjusted R-Squred value
Here,
- Adjusted R-squared value helps to balance between accuracy and model's complexity as it penalizes predictor with high complexity.
- It decreases overfitting by penalizing very complex models
- A good metric to compare multiple predictors, as R-squared Value will always increase with the complexity of the model. So a very complex model with always get higher R-squared Value than a less complex but more accurate and robust model.