I have just run a Linear regression model on the Dataset having 7 independent variable and 1 target variable. Below is the R squared and MSE values.
- Mean squared error for training set : 36530921.0123
- $R^2$ value for training set : 0.7477
Can anybody please give me some tips to increase the efficiency of this model.
Edit: I have just implemented the same problem using Linear regression with Normalization of the features. I got the below output: Mean squared error for training set : 5.468490570335696e-10 R2 value for training set : 0.9275088299658416 Mean squared error for training set : 4.111793316375822e-10 R2 value for training set : 0.9342888671422529
So can we consider normalizing the dataset to get better accuracy ?