Conformal Prediction of Customer Segment Memberships by Customer Type; Uncertainty, Quantified and Unquantified
This Blog Post: Conformal Prediction of Customer Segment Memberships by Customer Type; Uncertainty, Quantified and Unquantified © 2024 by Lynd Bacon & Loma Buena Associates is licensed under CC BY-NC-SA 4.0 TL;DR? Here’s the BLUF: Conformal prediction methods can provide statistically valid certainty guarantees when predicting class (e.g., segment) memberships, or other kinds of outcomes, that machine learning models are often used for predicting. Depending on how these methods are used, the quality of the results can depend on characteristics of the objects (e.g., customers) that predictions are for. When such characteristics consist of a priori known types or groups, investigating the quality of conformal prediction results for them is very straightforward. Conformal prediction is for quantifying uncertainty. Some kinds of uncertainty that decision-makers face may not be quantifiable. This conformal prediction niblet is a follow up to a pr...