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A company wants to build a model to predict whether a customer will buy a product from its online store based on some features. A data scientist was hired for this role in which he started collecting data from various sources to design a suitable model. He decided to use a complex model with all the features included and at the same time apply regularization. All features present in the model are important and he does not want to lose any feature while predicting the outcome. Which type of regularization technique should he use?