How to fine tune the regression model if it has high dimensional multi variate data

@RAVI761 wrote:

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

1. It has 6 variables in total. 5 of them features, 4 features are categorical.
2. Using Label encoding and tried other encoding techniques also.
3. Correlation factor among each of them was weak as all them are completely independent. Attached correlation matrix.
   
   corr_factor.PNG754×213 8.91 KB

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.

model_prediction.PNG830×407 9.74 KB

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

Posts: 1

Participants: 1

Read full topic