Why the lasso method in multinomial logistic regression differ from the traditional method using maximum likelihood? I found that the significant coefficients in lasso have different values against the regular one. The significant coefficients mean the coefficient included in the model. If i'm using the p value (sig.) of Wald test, the significant coefficient have p-value under 0.05(my alpha). The coefficient included using lasso and the traditional multinomial logistic regression are different, and have different values.
Why did that happened?