How do I interpret Lasso coefficients?

What do Lasso coefficients tell us about our model?

Lasso coefficients indicate the strength and direction of the relationship between predictors and the response variable. A coefficient close to zero suggests that the predictor has little to no effect.

How do I know if a coefficient is significant?

You can assess significance by looking at the absolute value of the coefficient and its corresponding p-value. In Lasso, coefficients that are shrunk to zero indicate less importance.

What happens if a coefficient is exactly zero?

If a coefficient is exactly zero, it means that the corresponding predictor variable is not included in the model, indicating it does not contribute to predicting the response variable.

Can I interpret Lasso coefficients the same way as Ridge coefficients?

Not exactly. While both methods regularize coefficients, Lasso can shrink some coefficients to zero, effectively performing variable selection, whereas Ridge tends to keep all coefficients but shrinks them.