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.
Uncovering hidden patterns in regional development using unsupervised learning.Environment and Planning B: Urban Analytics and City Science, 49(7):1970–1988
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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.