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ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning -- Additional Material
Pernille Matthews, Lena Krieger, Tommaso Amico +3
Clustering is an unsupervised technique for grouping data points by similarity. While explainability methods exist for supervised machine learning, they are not directly applicable…
DCFO: Density-Based Counterfactuals for Outliers -- Additional Material
Tommaso Amico, Pernille Matthews, Lena Krieger +2
Outlier detection identifies data points that significantly deviate from the majority of the data distribution. Explaining outliers is crucial for understanding the underlying fact…
Internal Evaluation of Density-Based Clusterings with Noise
Anna Beer, Lena Krieger, Pascal Weber +3
Being able to evaluate the quality of a clustering result even in the absence of ground truth cluster labels is fundamental for research in data mining. However, most cluster valid…
Ultrametric Cluster Hierarchies: I Want 'em All!
Andrew Draganov, Pascal Weber, Rasmus Skibdahl Melanchton Jørgensen +3
Hierarchical clustering is a powerful tool for exploratory data analysis, organizing data into a tree of clusterings from which a partition can be chosen. This paper generalizes th…
Temporal Subspace Clustering for Molecular Dynamics Data
Anna Beer, Martin Heinrigs, Claudia Plant +1
We introduce MOSCITO (MOlecular Dynamics Subspace Clustering with Temporal Observance), a subspace clustering for molecular dynamics data. MOSCITO groups those timesteps of a molec…