A Scalable Approach to Fuzzy Rough Nearest Neighbour Classification with Ordered Weighted Averaging Operators. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (IJCRS, 2019)

fuzzy-rough-learn 0.1: A Python Library for Machine Learning with Fuzzy Rough Sets. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (IJCRS, 2020)

Scalable Approximate FRNN-OWA Classification. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (IEEE Trans. Fuzzy Syst., 2020)

Adapting Fuzzy Rough Sets for Classification with Missing Values. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (IJCRS, 2021)

Average Localised Proximity: A new data descriptor with good default one-class classification performance. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (Pattern Recognit., 2021)

Fuzzy-rough-learn 0.2: a Python library for fuzzy rough set algorithms and one-class classification. - Oliver Urs Lenz; Chris Cornelis; Daniel Peralta (FUZZ-IEEE, 2022)

Representing missing values through polar encoding. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (CoRR, 2022)

Choquet-based fuzzy rough sets. - Adnan Theerens; Oliver Urs Lenz; Chris Cornelis (Int. J. Approx. Reason., 2022)

Optimised one-class classification performance. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (Mach. Learn., 2022)

No Imputation Without Representation. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (BNAIC/BENELEARN, 2023)

Classifying Token Frequencies Using Angular Minkowski p-Distance. - Oliver Urs Lenz; Chris Cornelis (IJCRS, 2023)

A unified weighting framework for evaluating nearest neighbour classification. - Oliver Urs Lenz; Henri Bollaert; Chris Cornelis (CoRR, 2023)

Directional anomaly detection. - Oliver Urs Lenz; Matthijs van Leeuwen (CoRR, 2024)

Polar Encoding: A Simple Baseline Approach for Classification With Missing Values. - Oliver Urs Lenz; Daniel Peralta; Chris Cornelis (IEEE Trans. Fuzzy Syst., 2024)