You are developing a machine learning model based on linear regression with over 100 input features. All feature values range between -1 and 1. You hypothesize that many of these features do not contribute meaningful information to the model's predictions. To streamline the model, you wish to remove these non-informative features while retaining the important ones in their original form. Which technique should you use?