Describe an application of Independent Component Analysis (ICA) to extract meaningful features from your dataset. Discuss the tradeoff between using linear or nonlinear ICA methods in this context.

We would apply ICA to whiten the correlated features and extract the independent components, which represent the underlying factors driving user behavior. We would use a nonlinear ICA method, such as kernel-based ICA, to capture complex relationships in the data that may not be linearly separable. This approach balances the need for simplicity with the requirement for accurate representation of non-linear patterns.