Consensus across univariate z-scores, Mahalanobis distance, Isolation Forest, Local Outlier Factor, and One-Class SVM identifies consistent multivariate outliers among European regions that reflect real structural differences rather than data errors.
Detecting structural breaks and spatial anomalies in regional development: A clustering perspective.Regional Science Policy and Practice, 10(4):377–394
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Unsupervised Machine Learning for Detecting Structural Anomalies in European Regional Statistics
Consensus across univariate z-scores, Mahalanobis distance, Isolation Forest, Local Outlier Factor, and One-Class SVM identifies consistent multivariate outliers among European regions that reflect real structural differences rather than data errors.