This report applies unsupervised learning methods, specifically association rule mining, to European Social Survey (ESS Round 10) data to explore social, political, and attitudinal patterns associated with low trust in parliament in Greece. The analysis emphasizes methodological justification, validation, and interpretation of associations.

This report applies unsupervised learning methods to World Development Indicators (WDI) data to explore latent global development structures. Principal Component Analysis (PCA) is used to reduce dimensionality and identify interpretable development dimensions, followed by hierarchical clustering in the reduced space to derive stable country groups. The analysis emphasizes methodological justification, validation, and interpretability.