Evaluation metrics are essential in selecting the most appropriate predictive model. Conventional metrics such as R-squared, root mean squared error (RMSE), and mean absolute percentage error (MAPE) rely on arithmetic averages, making them sensitive to outliers, undefined values, and scale...

The rare access to exact official geocoordinates opens new methodological possibilities for analyzing highly sensitive tax data. We explore their visualization potential and systematically evaluate aggregation as an anonymization strategy, with particular attention to its methodological and...

The availability of geocoordinates offers valuable insights into spatial patterns of economic, demographic and health outcomes. However, disclosing the exact geolocation of statistical units to secondary analysts contravenes the responsible use of data. To protect privacy, anonymisation methods...