Granular approximations: A novel statistical learning approach for handling data inconsistency with respect to a fuzzy relation

Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise

(2021) Sergio González et al.   NEUROCOMPUTING

Granular representation of OWA-based fuzzy rough sets

(2021) Marko Palangetić et al.   FUZZY SETS AND SYSTEMS

Rough set-based feature selection for weakly labeled data

(2021) Andrea Campagner et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

An Accelerator for Rule Induction in Fuzzy Rough Theory

(2021) Suyun Zhao et al.   IEEE TRANSACTIONS ON FUZZY SYSTEMS

Attribute reduction with fuzzy rough self-information measures

(2020) Changzhong Wang et al.   INFORMATION SCIENCES

Fuzzy extensions of the dominance-based rough set approach

(2020) Marko Palangetić et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Monotonic classification: An overview on algorithms, performance measures and data sets

(2019) José-Ramón Cano et al.   NEUROCOMPUTING

Fuzzy-Rough Instance Selection Combined with Effective Classifiers in Credit Scoring

(2017) ZhanFeng Liu et al.   NEURAL PROCESSING LETTERS

Ordinal Regression Methods: Survey and Experimental Study

(2016) Pedro Antonio Gutierrez et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Fuzzy-rough nearest neighbour classification and prediction

(2011) Richard Jensen et al.   THEORETICAL COMPUTER SCIENCE

Building a Rule-Based Classifier—A Fuzzy-Rough Set Approach

(2009) Suyun Zhao et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Stochastic dominance-based rough set model for ordinal classification

(2008) Wojciech Kotłowski et al.   INFORMATION SCIENCES