Label, Segment, Featurize : a reusable framework for prediction engineering
In this paper, we introduce “prediction engineering” as a formal step in the predictive modeling process. We define a generalizable 3 part framework — Label, Segment, Featurize (L-S-F) — to address the growing demand for predictive models. The framework provides abstractions for data scientists to customize the process to unique prediction problems. We describe how to apply the L-S-F framework to characteristic problems in 2 domains and demonstrate an implementation over 5 unique prediction problems…
Published in: IEEE International Conference on Data Science and Advanced Analytics 2016
