Within the statistical and machine learning literature, regularization techniques are often used to construct sparse (predictive) models. Most strategies only work for data where all predictors treated identically, such as Lasso regression (continuous) linear effects. However, many predictive problems involve different types of require a tailored term. We propose multi-type penalty that acts on...
