# How to Improve an Elastic Net Model?

I have a dataset with $$n=1500$$ observations and $$p=2700$$ variables.
I fitted an Elastic Net model with $$\alpha=0.4$$ and $$\lambda=0.1$$
I chose the $$\lambda$$ with cross validation, and the $$\alpha$$ and $$\lambda$$ values that gave the lowest RMSE (0.88 for the test set).

from the plot of observed vs predicted the model is not a great fit.

How can I improve my model?

• This could be a problem of scaling your variables (incorrectly). – Arya McCarthy Jun 11 at 16:33
• I used the R function of glmnet, which standardizes the variables. I also try to standardize on my own and set standardize=False, but got the same results. – ari6739 Jun 11 at 17:39

• Do you mean $Y \sim predict(model)$ ? the plot looks a bit better. but, is there a way to change the original model to fit better? – ari6739 Jun 11 at 16:17