12 papers
Estimating Community Boundaries in Geometric Random Graphs
Taha Ameen, Neeladri Maitra
The unit square is divided into two rectangles by the vertical line , where . Consider independent uniformly distributed points on , which we int…
An Empirical Study of Feature Selection Granularity
Muhammad Rajabinasab, Arthur Zimek
Feature selection aims to identify the most informative and relevant features for a given dataset, either in terms of capturing the underlying data structure and distribution bette…
Worse than Random: The Importance of a Baseline for Unsupervised Feature Selection
Muhammad Rajabinasab, Michael E. Houle, Oussama Chelly +1
Many novel unsupervised feature selection methods are proposed each year, yet their empirical evaluation is limited to supervised and unsupervised evaluation metrics computed on se…
FSEVAL: Feature Selection Evaluation Toolbox and Dashboard
Muhammad Rajabinasab, Arthur Zimek
Feature selection is a fundamental machine learning and data mining task, involved with discriminating redundant features from informative ones. It is an attempt to address the cur…
Disjoint Generation of Synthetic Data
Anton Danholt Lautrup, Muhammad Rajabinasab, Tobias Hyrup +2
We propose a new framework for generating tabular synthetic datasets via disjoint generative models. In this paradigm, a dataset is partitioned into disjoint subsets that are suppl…
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…