Statistical Analysis and Data Mining: The ASA Data Science Journal
source link: https://onlinelibrary.wiley.com/doi/abs/10.1002/sam.11389
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Rotational grid, PAI‐maximizing crime forecasts
Abstract
Crime forecasts are sensitive to the spatial discretizations on which they are defined. Furthermore, while the Predictive Accuracy Index (PAI) is a common evaluation metric for crime forecasts, most crime forecasting methods are optimized using maximum likelihood or other smooth optimization techniques. Here we present a novel methodology that jointly (1) selects an optimal grid size and orientation and (2) learns a scoring function with the aim of directly maximizing PAI. Our method was one of the top performing submissions in the 2017 NIJ Crime Forecasting challenge, winning 9 of the 20 PAI categories under the name of team PASDA. We illustrate the model on data provided through the competition from the Portland Police Department.
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