Comparison of the Rough Sets Approach and Probabilistic Data Analysis Techniques on a Common Set of Medical Data. - Ewa Krusinska; Ankica Babic; Roman Slowinski; Jerzy Stefanowski (Intelligent Decision Support, 1992)

Analysis of Diagnostic Symptoms in Vibroacoustic Diagnostics by Means of the Rough Sets Theory. - Ryszard Nowicki; Roman Slowinski; Jerzy Stefanowski (Intelligent Decision Support, 1992)

'Roughdas' and 'Roughclass' Software Implementations of the Rough Sets Approach. - Roman Slowinski; Jerzy Stefanowski (Intelligent Decision Support, 1992)

The Rough Sets Approach to Knowledge Analysis for Classification Support in Technical Diagnostics of Mechanical Objects. - Jerzy Stefanowski; Roman Slowinski; Ryszard Nowicki (IEA/AIE, 1992)

Neural Networks and Rough Sets - Comparison and Combination for Classification of Histological Pictures. - Jacek Jelonek; Krzysztof Krawiec; Roman Slowinski; Jerzy Stefanowski; Janusz Szymas (RSKD, 1993)

Handling Various Types of Uncertainty in the Rough Set Approach. - Roman Slowinski; Jerzy Stefanowski (RSKD, 1993)

A General Two-Stage Approach to Inducing Rules from Examples. - Jerzy Stefanowski; Daniel Vanderpooten (RSKD, 1993)

Rough-Set Reasoning about Uncertain Data. - Roman Slowinski; Jerzy Stefanowski (Fundam. Informaticae, 1996)

Rough Sets: Facts Versus Misconceptions. - Jerzy W. Grzymala-Busse; Jerzy Stefanowski; Wojciech Ziarko (Informatica (Slovenia), 1996)

Rough Set Theory and Rule Induction Techniques for Discovery of Attribute Dependencies in Medical Information Systems. - Jerzy Stefanowski; Krzysztof Slowinski (PKDD, 1997)

Feature subset selection for classification of histological images. - Jacek Jelonek; Jerzy Stefanowski (Artif. Intell. Medicine, 1997)

Experiments on Solving Multiclass Learning Problems by n2-classifier. - Jacek Jelonek; Jerzy Stefanowski (ECML, 1998)

ROSE - Software Implementation of the Rough Set Theory. - Bartlomiej Predki; Roman Slowinski; Jerzy Stefanowski; Robert Susmaga; Szymon Wilk (Rough Sets and Current Trends in Computing, 1998)

Handling Continuous Attributes in Discovery of Strong Decision Rules. - Jerzy Stefanowski (Rough Sets and Current Trends in Computing, 1998)

On the Extension of Rough Sets under Incomplete Information. - Jerzy Stefanowski; Alexis Tsoukiàs (RSFDGrC, 1999)

Variable Consistency Model of Dominance-Based Rough Sets Approach. - Salvatore Greco; Benedetto Matarazzo; Roman Slowinski; Jerzy Stefanowski (Rough Sets and Current Trends in Computing, 2000)

An Algorithm for Induction of Decision Rules Consistent with the Dominance Principle. - Salvatore Greco; Benedetto Matarazzo; Roman Slowinski; Jerzy Stefanowski (Rough Sets and Current Trends in Computing, 2000)

Valued Tolerance and Decision Rules. - Jerzy Stefanowski; Alexis Tsoukiàs (Rough Sets and Current Trends in Computing, 2000)

Incomplete Information Tables and Rough Classification. - Jerzy Stefanowski; Alexis Tsoukiàs (Comput. Intell., 2001)

Three discretization methods for rule induction. - Jerzy W. Grzymala-Busse; Jerzy Stefanowski (Int. J. Intell. Syst., 2001)

Induction of decision rules in classification and discovery-oriented perspectives. - Jerzy Stefanowski; Daniel Vanderpooten (Int. J. Intell. Syst., 2001)

Evaluating business credit risk by means of approach-integrating decision rules and case-based learning. - Jerzy Stefanowski; Szymon Wilk (Intell. Syst. Account. Finance Manag., 2001)

Bagging and Induction of Decision Rules. - Jerzy Stefanowski (Intelligent Information Systems, 2002)

Mining Association Rules in Preference-Ordered Data. - Salvatore Greco; Roman Slowinski; Jerzy Stefanowski (ISMIS, 2002)

Importance and Interaction of Conditions in Decision Rules. - Salvatore Greco; Benedetto Matarazzo; Roman Slowinski; Jerzy Stefanowski (Rough Sets and Current Trends in Computing, 2002)

Induction of Decision Rules and Classification in the Valued Tolerance Approach. - Jerzy Stefanowski; Alexis Tsoukiàs (Rough Sets and Current Trends in Computing, 2002)

Application of Rule Induction and Rough Sets to Verification of Magnetic Resonance Diagnosis. - Krzysztof Slowinski; Jerzy Stefanowski; Dariusz Siwinski (Fundam. Informaticae, 2002)

Carrot and Language Properties in Web Search Results Clustering. - Jerzy Stefanowski; Dawid Weiss (AWIC, 2003)

Incremental Rule Induction for Multicriteria and Multiattribute Classification. - Jerzy Stefanowski; Marcin Zurawski (IIS, 2003)

Web Search Results Clustering in Polish: Experimental Evaluation of Carrot. - Dawid Weiss; Jerzy Stefanowski (IIS, 2003)

Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition. - Stanislaw Osinski; Jerzy Stefanowski; Dawid Weiss (Intelligent Information Systems, 2004)

The Bagging and n2-Classifiers Based on Rules Induced by MODLEM. - Jerzy Stefanowski (Rough Sets and Current Trends in Computing, 2004)

An experimental evaluation of improving rule based classifiers with two approaches that change representations of learning examples. - Jerzy Stefanowski (Eng. Appl. Artif. Intell., 2004)

Hyperplane Aggregation of Dominance Decision Rules. - Roman Pindur; Robert Susmaga; Jerzy Stefanowski (Fundam. Informaticae, 2004)

Incremental versus Non-incremental Rule Induction for Multicriteria Classification. - Salvatore Greco; Roman Slowinski; Jerzy Stefanowski; Marcin Zurawski (Trans. Rough Sets, 2004)

Rough Set Theory and Decision Rules in Data Analysis of Breast Cancer Patients. - Jerzy Zaluski; Renata Szoszkiewicz; Jerzy Krysinski; Jerzy Stefanowski (Trans. Rough Sets, 2004)

Mining Context Based Sequential Patterns. - Jerzy Stefanowski; Radoslaw Z. Ziembinski (AWIC, 2005)

On Using Rule Induction in Multiple Classifiers with a Combiner Aggregation Strategy. - Jerzy Stefanowski; Slawomir Nowaczyk (ISDA, 2005)

A Comparison of Two Approaches to Data Mining from Imbalanced Data. - Jerzy W. Grzymala-Busse; Jerzy Stefanowski; Szymon Wilk (J. Intell. Manuf., 2005)

Classification of Polish Email Messages: Experiments with Various Data Representations. - Jerzy Stefanowski; Marcin Zienkowicz (ISMIS, 2006)

Preface. - Mariusz Flasinski; Edward Nawarecki; Lech Polkowski; Robert Schaefer; Jerzy Stefanowski; Zbigniew Suraj (Fundam. Informaticae, 2006)

An Empirical Study of Using Rule Induction and Rough Sets to Software Cost Estimation. - Jerzy Stefanowski (Fundam. Informaticae, 2006)

Rough Sets for Handling Imbalanced Data: Combining Filtering and Rule-based Classifiers. - Jerzy Stefanowski; Szymon Wilk (Fundam. Informaticae, 2006)

Comprehensible and Accurate Cluster Labels in Text Clustering. - Jerzy Stefanowski; Dawid Weiss (RIAO, 2007)

Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles. - Jerzy Stefanowski (RSEISP, 2007)

Evaluating Importance of Conditions in the Set of Discovered Rules. - Salvatore Greco; Roman Slowinski; Jerzy Stefanowski (RSFDGrC, 2007)

On Combined Classifiers, Rule Induction and Rough Sets. - Jerzy Stefanowski (Trans. Rough Sets, 2007)

Selective Pre-processing of Imbalanced Data for Improving Classification Performance. - Jerzy Stefanowski; Szymon Wilk (DaWaK, 2008)

Ensembles of Abstaining Classifiers Based on Rule Sets. - Jerzy Blaszczynski; Jerzy Stefanowski; Magdalena Zajac (ISMIS, 2009)

An experimental evaluation of two approaches to mining context based sequential patterns. - Jerzy Stefanowski; Radoslaw Z. Ziembinski (Control. Cybern., 2009)

Integrating Selective Pre-processing of Imbalanced Data with Ivotes Ensemble. - Jerzy Blaszczynski; Magdalena Deckert; Jerzy Stefanowski; Szymon Wilk (RSCTC, 2010)

Ordinal Classification with Monotonicity Constraints by Variable Consistency Bagging. - Jerzy Blaszczynski; Roman Slowinski; Jerzy Stefanowski (RSCTC, 2010)

Argument Based Generalization of MODLEM Rule Induction Algorithm. - Krystyna Napierala; Jerzy Stefanowski (RSCTC, 2010)

Learning from Imbalanced Data in Presence of Noisy and Borderline Examples. - Krystyna Napierala; Jerzy Stefanowski; Szymon Wilk (RSCTC, 2010)

Variable Consistency Bagging Ensembles. - Jerzy Blaszczynski; Roman Slowinski; Jerzy Stefanowski (Trans. Rough Sets, 2010)

Local neighbourhood extension of SMOTE for mining imbalanced data. - Tomasz Maciejewski; Jerzy Stefanowski (CIDM, 2011)

Accuracy Updated Ensemble for Data Streams with Concept Drift. - Dariusz Brzezinski; Jerzy Stefanowski (HAIS (2), 2011)

Comparing Block Ensembles for Data Streams with Concept Drift. - Magdalena Deckert; Jerzy Stefanowski (ADBIS Workshops, 2012)

Identification of Different Types of Minority Class Examples in Imbalanced Data. - Krystyna Napierala; Jerzy Stefanowski (HAIS (2), 2012)

Modifications of Classification Strategies in Rule Set Based Bagging for Imbalanced Data. - Krystyna Napierala; Jerzy Stefanowski (HAIS (2), 2012)

IIvotes ensemble for imbalanced data. - Jerzy Blaszczynski; Magdalena Deckert; Jerzy Stefanowski; Szymon Wilk (Intell. Data Anal., 2012)

BRACID: a comprehensive approach to learning rules from imbalanced data. - Krystyna Napierala; Jerzy Stefanowski (J. Intell. Inf. Syst., 2012)

Extending Bagging for Imbalanced Data. - Jerzy Blaszczynski; Jerzy Stefanowski; Lukasz Idkowiak (CORES, 2013)

Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering. - José A. Sáez; Julián Luengo; Jerzy Stefanowski; Francisco Herrera (IDEAL, 2014)

RILL: Algorithm for Learning Rules from Streaming Data with Concept Drift. - Magdalena Deckert; Jerzy Stefanowski (ISMIS, 2014)

Local Characteristics of Minority Examples in Pre-processing of Imbalanced Data. - Jerzy Stefanowski; Krystyna Napierala; Malgorzata Trzcielinska (ISMIS, 2014)

Prequential AUC for Classifier Evaluation and Drift Detection in Evolving Data Streams. - Dariusz Brzezinski; Jerzy Stefanowski (NFMCP, 2014)

The Impact of Local Data Characteristics on Learning from Imbalanced Data. - Jerzy Stefanowski (RSEISP, 2014)

Combining block-based and online methods in learning ensembles from concept drifting data streams. - Dariusz Brzezinski; Jerzy Stefanowski (Inf. Sci., 2014)

Processing and mining complex data streams. - Jerzy Stefanowski; Alfredo Cuzzocrea; Dominik Slezak (Inf. Sci., 2014)

Open challenges for data stream mining research. - Georg Krempl; Indre Zliobaite; Dariusz Brzezinski; Eyke Hüllermeier; Mark Last; Vincent Lemaire 001; Tino Noack; Ammar Shaker; Sonja Sievi; Myra Spiliopoulou; Jerzy Stefanowski (SIGKDD Explor., 2014)

Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm. - Dariusz Brzezinski; Jerzy Stefanowski (IEEE Trans. Neural Networks Learn. Syst., 2014)

On Properties of Undersampling Bagging and Its Extensions for Imbalanced Data. - Jerzy Stefanowski (CORES, 2015)

The Usefulness of Roughly Balanced Bagging for Complex and High-Dimensional Imbalanced Data. - Mateusz Lango; Jerzy Stefanowski (NFMCP, 2015)

Adaptive Ensembles for Evolving Data Streams - Combining Block-Based and Online Solutions. - Jerzy Stefanowski (NFMCP, 2015)

Addressing imbalanced data with argument based rule learning. - Krystyna Napierala; Jerzy Stefanowski (Expert Syst. Appl., 2015)

Abstaining in rule set bagging for imbalanced data. - Krystyna Napierala; Jerzy Stefanowski (Log. J. IGPL, 2015)

Neighbourhood sampling in bagging for imbalanced data. - Jerzy Blaszczynski; Jerzy Stefanowski (Neurocomputing, 2015)

Data stream classification and big data analytics. - Bartosz Krawczyk; Jerzy Stefanowski; Michal Wozniak 001 (Neurocomputing, 2015)

SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering. - José A. Sáez; Julián Luengo; Jerzy Stefanowski; Francisco Herrera (Inf. Sci., 2015)

Ensemble Diversity in Evolving Data Streams. - Dariusz Brzezinski; Jerzy Stefanowski (DS, 2016)

Application of Preprocessing Methods to Imbalanced Clinical Data: An Experimental Study. - Szymon Wilk; Jerzy Stefanowski; Szymon Wojciechowski; Ken J. Farion; Wojtek Michalowski (ITIB (1), 2016)

Increasing the Interpretability of Rules Induced from Imbalanced Data by Using Bayesian Confirmation Measures. - Krystyna Napierala; Jerzy Stefanowski; Izabela Szczech (NFMCP@PKDD/ECML, 2016)

Consistency Driven Feature Subspace Aggregating for Ordinal Classification. - Jerzy Blaszczynski; Jerzy Stefanowski; Roman Slowinski (IJCRS, 2016)

PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis. - Mateusz Lango; Dariusz Brzezinski; Jerzy Stefanowski (SemEval@NAACL-HLT, 2016)

Post-processing of BRACID Rules Induced from Imbalanced Data. - Krystyna Napierala; Jerzy Stefanowski (Fundam. Informaticae, 2016)

Types of minority class examples and their influence on learning classifiers from imbalanced data. - Krystyna Napierala; Jerzy Stefanowski (J. Intell. Inf. Syst., 2016)

Dealing with Data Difficulty Factors While Learning from Imbalanced Data. - Jerzy Stefanowski (Challenges in Computational Statistics and Data Mining, 2016)

An Algorithm for Selective Preprocessing of Multi-class Imbalanced Data. - Szymon Wojciechowski; Szymon Wilk; Jerzy Stefanowski (CORES, 2017)

Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data. - Mateusz Lango; Dariusz Brzezinski; Sebastian Firlik; Jerzy Stefanowski (DS, 2017)

Actively Balanced Bagging for Imbalanced Data. - Jerzy Blaszczynski; Jerzy Stefanowski (ISMIS, 2017)

Evaluating Difficulty of Multi-class Imbalanced Data. - Mateusz Lango; Krystyna Napierala; Jerzy Stefanowski (ISMIS, 2017)

Tetrahedron: Barycentric Measure Visualizer. - Dariusz Brzezinski; Jerzy Stefanowski; Robert Susmaga; Izabela Szczech (ECML/PKDD (3), 2017)

Exploring complex and big data. - Jerzy Stefanowski; Krzysztof Krawiec; Robert Wrembel (Int. J. Appl. Math. Comput. Sci., 2017)

Visual-Based Analysis of Classification Measures with Applications to Imbalanced Data. - Dariusz Brzezinski; Jerzy Stefanowski; Robert Susmaga; Izabela Szczech (CoRR, 2017)

Ensemble learning for data stream analysis: A survey. - Bartosz Krawczyk; Leandro L. Minku; João Gama 001; Jerzy Stefanowski; Michal Wozniak 001 (Inf. Fusion, 2017)

Prequential AUC: properties of the area under the ROC curve for data streams with concept drift. - Dariusz Brzezinski; Jerzy Stefanowski (Knowl. Inf. Syst., 2017)

Stream Classification. - Jerzy Stefanowski; Dariusz Brzezinski (Encyclopedia of Machine Learning and Data Mining, 2017)

Local Data Characteristics in Learning Classifiers from Imbalanced Data. - Jerzy Blaszczynski; Jerzy Stefanowski (Advances in Data Analysis with Computational Intelligence Methods, 2018)

ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information. - Mateusz Lango; Dariusz Brzezinski; Jerzy Stefanowski (LIDTA@ECML/PKDD, 2018)

Visual-based analysis of classification measures and their properties for class imbalanced problems. - Dariusz Brzezinski; Jerzy Stefanowski; Robert Susmaga; Izabela Szczech (Inf. Sci., 2018)

Multi-class and feature selection extensions of Roughly Balanced Bagging for imbalanced data. - Mateusz Lango; Jerzy Stefanowski (J. Intell. Inf. Syst., 2018)

Improving Bagging Ensembles for Class Imbalanced Data by Active Learning. - Jerzy Blaszczynski; Jerzy Stefanowski (Advances in Feature Selection for Data and Pattern Recognition, 2018)

Using Information on Class Interrelations to Improve Classification of Multiclass Imbalanced Data: A New Resampling Algorithm. - Malgorzata Janicka; Mateusz Lango; Jerzy Stefanowski (Int. J. Appl. Math. Comput. Sci., 2019)

multi-imbalance: Open Source Python Toolbox for Multi-class Imbalanced Classification. - Jacek Grycza; Damian Horna; Hanna Klimczak; Mateusz Lango; Kamil Plucinski; Jerzy Stefanowski (ECML/PKDD (5), 2020)

On the Dynamics of Classification Measures for Imbalanced and Streaming Data. - Dariusz Brzezinski; Jerzy Stefanowski; Robert Susmaga; Izabela Szczech (IEEE Trans. Neural Networks Learn. Syst., 2020)

Two Ways of Extending BRACID Rule-based Classifiers for Multi-class Imbalanced Data. - Maria Naklicka; Jerzy Stefanowski (LIDTA@ECML/PKDD, 2021)

Time Aspect in Making an Actionable Prediction of a Conversation Breakdown. - Piotr Janiszewski; Mateusz Lango; Jerzy Stefanowski (ECML/PKDD (5), 2021)

Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification. - Kamil Plucinski; Mateusz Lango; Jerzy Stefanowski (PKDD/ECML Workshops (1), 2021)

Classification of Multi-class Imbalanced Data: Data Difficulty Factors and Selected Methods for Improving Classifiers. - Jerzy Stefanowski (IJCRS, 2021)

The impact of data difficulty factors on classification of imbalanced and concept drifting data streams. - Dariusz Brzezinski; Leandro L. Minku; Tomasz Pewinski; Jerzy Stefanowski; Artur Szumaczuk (Knowl. Inf. Syst., 2021)

Quality Versus Speed in Energy Demand Prediction - Experience Report from an R &D project. - Witold Andrzejewski; Jedrzej Potoniec; Maciej Drozdowski; Jerzy Stefanowski; Robert Wrembel; Pawel Stapf (DEXA (1), 2022)

The Influence of Multiple Classes on Learning from Imbalanced Data Streams. - Agnieszka Lipska; Jerzy Stefanowski (LIDTA, 2022)

Quality versus speed in energy demand prediction for district heating systems. - Witold Andrzejewski; Jedrzej Potoniec; Maciej Drozdowski; Jerzy Stefanowski; Robert Wrembel; Pawel Stapf (CoRR, 2022)

The Influence of Multiple Classes on Learning Online Classifiers from Imbalanced and Concept Drifting Data Streams. - Agnieszka Lipska; Jerzy Stefanowski (CoRR, 2022)

What makes multi-class imbalanced problems difficult? An experimental study. - Mateusz Lango; Jerzy Stefanowski (Expert Syst. Appl., 2022)

Multi-criteria Approaches to Explaining Black Box Machine Learning Models. - Jerzy Stefanowski (ACIIDS (2), 2023)

The Problem of Coherence in Natural Language Explanations of Recommendations. - Jakub Raczynski; Mateusz Lango; Jerzy Stefanowski (ECAI, 2023)

Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. - Damian Horna; Mateusz Lango; Jerzy Stefanowski (LIDTA, 2023)

PIQARD System for Experimenting and Testing Language Models with Prompting Strategies. - Marcin Korcz; Dawid Plaskowski; Mateusz Politycki; Jerzy Stefanowski; Alex Terentowicz (ECML/PKDD (7), 2023)

Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues. - Riccardo Albertoni; Sara Colantonio; Piotr Skrzypczynski; Jerzy Stefanowski (CoRR, 2023)

Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. - Patryk Wielopolski; Oleksii Furman; Jerzy Stefanowski; Maciej Zieba (ECAI, 2024)

Towards Differentiating Between Failures and Domain Shifts in Industrial Data Streams. - Natalia Wojak-Strzelecka; Szymon Bobek; Grzegorz J. Nalepa; Jerzy Stefanowski (HAII5.0@ECAI, 2024)

A multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. - Ignacy Stepka; Mateusz Lango; Jerzy Stefanowski (Int. J. Appl. Math. Comput. Sci., 2024)

Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels. - Patryk Wielopolski; Oleksii Furman; Jerzy Stefanowski; Maciej Zieba (CoRR, 2024)

A-PETE: Adaptive Prototype Explanations of Tree Ensembles. - Jacek Karolczak; Jerzy Stefanowski (CoRR, 2024)

Improving Online Bagging for Complex Imbalanced Data Stream. - Bartosz Przybyl; Jerzy Stefanowski (CoRR, 2024)

Properties of Fairness Measures in the Context of Varying Class Imbalance and Protected Group Ratios. - Dariusz Brzezinski; Julia Stachowiak; Jerzy Stefanowski; Izabela Szczech; Robert Susmaga; Sofya Aksenyuk; Uladzimir Ivashka; Oleksandr Yasinskyi (ACM Trans. Knowl. Discov. Data, 2024)

Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change. - Ignacy Stepka; Jerzy Stefanowski; Mateusz Lango (KDD (1), 2025)

Towards Fairness for the Right Reasons: Using Saliency Maps to Evaluate Bias Removal in Neural Networks. - Lukasz Sztukiewicz; Ignacy Stepka; Michal Wilinski; Jerzy Stefanowski (CoRR, 2025)

DetoxAI: a Python Toolkit for Debiasing Deep Learning Models in Computer Vision. - Ignacy Stepka; Lukasz Sztukiewicz; Michal Wilinski; Jerzy Stefanowski (CoRR, 2025)

This part looks alike this: identifying important parts of explained instances and prototypes. - Jacek Karolczak; Jerzy Stefanowski (CoRR, 2025)