Design an extension to the existing linear regression model to represent nonlinear interactions between input features in your recommender system. Explain the underlying mathematical concept.

Apply a feature transformation using a function φ(x) to the input data before feeding it into the logistic regression model. This enables the model to capture higher-order relationships and interactions between input variables, effectively overcoming its limited capacity as a linear function approximator.