Elastic net uses a weighted combination of the L1 and L2 penalties that are used in both LASSO and Ridge regression, respectively.
LASSO performs feature selection by shrinking the coefficients of variables to zero
If a primary interest is to conduct automatic variable selection, only LASSO can do that.
One of the main drawbacks of deep learning is that it is more prone to overfitting
C (regularization parameter), Kernel Function, Gamma (RBF kernel)