A research-driven analysis of dynamic ticket pricing, modeling distributions with scaled Beta estimates derived from limited statistics (min, max, mean, median). The approach enriches Random Forest classification by incorporating shape parameters (α, β) and leveraging constant-value features for implicit regularization. Based on SeatGeek data.
random-forest parameter-estimation time-series-classification moment-matching implicit-regularization ticket-pricing scaled-beta-distribution quantile-matching ticket-resale feature-dilution
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Updated
Dec 24, 2025 - Jupyter Notebook