Advanced Optimization for Final Selection

Apply association rule mining to a dataset of photoshoot outfits to discover pairing rules (e.g., {Balconette Bra} -> {Thong Bottom}) and evaluate them using support, confidence, and lift.

Predict a model's rating for an unseen lingerie piece by applying user-based collaborative filtering, using a ratings matrix from other models with similar tastes.

Formulate the fitting room tryout process as an optimal stopping problem to maximize the chance of selecting the single best lingerie piece from a sequence.

Apply the 1/e optimal stopping rule to solve a numerical problem: given 15 lingerie pieces to try on sequentially, determine how many to 'scout' before being ready to select the best one.