why is regularization of coefficient magnitude used in linear regression why does regularization of coefficient magnitude improve the generalization of regression why does regularization of coefficient magnitude improve the generalization of regression? why does regularization of coefficient magnitude improve the generalization of linear regression which of the following functions can be used to enforce smoothness in linear regression what is tikhonov matrix what type of operator is used to enforce smoothness of the vector why does regularization of coefficient magnitude improve the generalization of linear regression why does regularization of coefficient magnitude improve the generalization of the regression equation? why does regularization improve the generalization of linear regression what is the basic argument upon which ridge and lasso regression are based on what is regularization tikhonov matrix why does regularization of coefficient magnitude improve the generalization of linear regression? why does regularization of coefficient magnitude improve the generalization of linear regression? why is tikhonov used for linear regression why is regularization of coefficient magnitude more appealing why is regularization better why does regularization of coefficient magnitude improve generalization of linear regression? is tikhonov a regularization matrix why does regularization of coefficient magnitude improve the generalization of linear regression?