Supervised Sequence Analysis (SSA) for High Dimensional Discovery of Predictive Histories for Health and Economic Outcomes

• In Event: Bridging Prediction and Inference

Brief Overview

We develop a supervised sequence analysis method that links interpretable groupings of historical data to predictive outcomes. This approach handles high-dimensional, sparse data and yields transparent profiles useful for forecasting.

Authors

• Adeline Lo, University of Wisconsin–Madison

• Héctor Pifarré i Arolas, University of Wisconsin–Madison

• Keith Levin, University of Wisconsin–Madison