Design and operationalize outcome models that compress noisy event histories into calibrated forecasts and constrained decisions. Use when a user asks about feature reduction, probability, expected value, aggregation, or moving a prediction method between sports, business, sales, advertising, financ
Design and operationalize outcome models that compress noisy event histories into calibrated forecasts and constrained decisions. Use when a user asks about feature reduction, probability, expected value, aggregation, or moving a prediction method between sports, business, sales, advertising, finance, or prediction markets. Load a domain adapter when one fits.