Regularization, Overfitting, Dropout Regularization, Early Stopping, Elastic Net.
the absolute value of the weight coefficients: It tends to shrink some of the weight coefficients to zero. The sum of the term is multiplied by lambda, which controls the amount of regularization. If lambda is too high, the model will be simple, and the risk of underfitting arises. L2