I am working on a regression problem(Non linear). The overview of the problem is like the below;

- It has 6 variables in total. 5 of them features, 4 features are categorical.
- Using Label encoding and tried other encoding techniques also.
- Correlation factor among each of them was weak as all them are completely independent. Attached correlation matrix.

I have tried polynomial regression(tried up to 3rd degree), Lasso & Ridge regression. RMSE is 1.48 to 1.50 for all of them almost same.

Can any one from community help me to increase the model performance. should i use neural network or tune the hyper parameters for the used algorithms.

Any guidance would be greatly appreciated