Human Rights Violations and Machine Learning - Cluster Analysis of Countries using the CIRIGHTS Dataset
This master's thesis explores the use of unsupervised machine learning techniques to cluster countries based on their degree of human rights violations. Accordingly, the study evaluates the performance of two clustering methods, K-Means clustering and Latent Class Analysis (LCA), using two cluster validation metrics (Silhouette Coefficient and Dunn Index), as well as an Accuracy measure using
