Regression is a type of machine learning task which measures the relationship between variables and outputs an estimation for a numeric variable. There are various regression algorithms which output a numeric value, e.g. the estimated value of a good/service price.
In machine learning, regularization is a method by which the ML model cost/error function is changed, to include an extra variable called the regularization hyperparameter. There are two basic types of regularization: L1-norm (lasso regression) and L2-norm (ridge regression). The lasso regularization uses the L1 norm parameter. The lasso regularized cost function is calculated as ... Read more