Jerzy Stefanowski

149 papers A 2B 4C 11Journal 63Unranked 60

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An interpretable prototype parts-based neural network for medical tabular data. CoRR Jacek Karolczak, Jerzy Stefanowski
2026	J	`jnl`	Explaining data changes with prototypes: A measure-driven approach. Inf. Fusion Jacek Karolczak, Jerzy Stefanowski
2026	J	`jnl`	Towards Differentiating Between Failures and Domain Shifts in Industrial Data Streams. CoRR Natalia Wojak-Strzelecka, Szymon Bobek, Grzegorz J. Nalepa, Jerzy Stefanowski
2025	—	`conf`	Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change. KDD (1) Ignacy Stepka, Jerzy Stefanowski, Mateusz Lango
2025	—	`conf`	DetoxAI: A Python Toolkit for Debiasing Deep Learning Models in Computer Vision. ECML/PKDD (10) Ignacy Stepka, Lukasz Sztukiewicz, Michal Wilinski, Jerzy Stefanowski
2025	J	`jnl`	DetoxAI: a Python Toolkit for Debiasing Deep Learning Models in Computer Vision. CoRR Ignacy Stepka, Lukasz Sztukiewicz, Michal Wilinski, Jerzy Stefanowski
2025	J	`jnl`	Explaining Concept Drift through the Evolution of Group Counterfactuals. CoRR Ignacy Stepka, Jerzy Stefanowski
2025	—	`conf`	Investigating the Relationship Between Debiasing and Artifact Removal using Saliency Maps. xAI (Late-breaking Work, Demos, Doctoral Consortium) Lukasz Sztukiewicz, Ignacy Stepka, Michal Wilinski, Jerzy Stefanowski
2025	—	`conf`	This Part Looks Alike This: Tdentifying Important Parts of Explained Instances and Prototypes. xAI (Late-breaking Work, Demos, Doctoral Consortium) Jacek Karolczak, Jerzy Stefanowski
2025	J	`jnl`	This part looks alike this: identifying important parts of explained instances and prototypes. CoRR Jacek Karolczak, Jerzy Stefanowski
2025	J	`jnl`	Towards Fairness for the Right Reasons: Using Saliency Maps to Evaluate Bias Removal in Neural Networks. CoRR Lukasz Sztukiewicz, Ignacy Stepka, Michal Wilinski, Jerzy Stefanowski
2024	J	`jnl`	A multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. Int. J. Appl. Math. Comput. Sci. Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski
2024	J	`jnl`	A-PETE: Adaptive Prototype Explanations of Tree Ensembles. CoRR Jacek Karolczak, Jerzy Stefanowski
2024	J	`jnl`	Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change. CoRR Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski
2024	J	`jnl`	Improving Online Bagging for Complex Imbalanced Data Stream. CoRR Bartosz Przybyl, Jerzy Stefanowski
2024	J	`jnl`	Multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. CoRR Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski
2024	A	`conf`	Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. ECAI Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba
2024	J	`jnl`	Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. CoRR Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba
2024	J	`jnl`	Properties of Fairness Measures in the Context of Varying Class Imbalance and Protected Group Ratios. ACM Trans. Knowl. Discov. Data Dariusz Brzezinski, Julia Stachowiak, Jerzy Stefanowski, Izabela Szczech, Robert Susmaga, Sofya Aksenyuk, Uladzimir Ivashka, Oleksandr Yasinskyi
2024	J	`jnl`	Properties of fairness measures in the context of varying class imbalance and protected group ratios. CoRR Dariusz Brzezinski, Julia Stachowiak, Jerzy Stefanowski, Izabela Szczech, Robert Susmaga, Sofya Aksenyuk, Uladzimir Ivashka, Oleksandr Yasinskyi
2024	—	`conf`	Towards Differentiating Between Failures and Domain Shifts in Industrial Data Streams. HAII5.0@ECAI Natalia Wojak-Strzelecka, Szymon Bobek, Grzegorz J. Nalepa, Jerzy Stefanowski
2024	J	`jnl`	Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels. CoRR Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba
2023	—	`conf`	Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. LIDTA Damian Horna, Mateusz Lango, Jerzy Stefanowski
2023	J	`jnl`	Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. CoRR Damian Horna, Mateusz Lango, Jerzy Stefanowski
2023	—	`conf`	Multi-criteria Approaches to Explaining Black Box Machine Learning Models. ACIIDS (2) Jerzy Stefanowski
2023	—	`conf`	PIQARD System for Experimenting and Testing Language Models with Prompting Strategies. ECML/PKDD (7) Marcin Korcz, Dawid Plaskowski, Mateusz Politycki, Jerzy Stefanowski, Alex Terentowicz
2023	J	`jnl`	Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues. CoRR Riccardo Albertoni, Sara Colantonio, Piotr Skrzypczynski, Jerzy Stefanowski
2023	A	`conf`	The Problem of Coherence in Natural Language Explanations of Recommendations. ECAI Jakub Raczynski, Mateusz Lango, Jerzy Stefanowski
2023	J	`jnl`	The Problem of Coherence in Natural Language Explanations of Recommendations. CoRR Jakub Raczynski, Mateusz Lango, Jerzy Stefanowski
2022	—	`conf`	Quality Versus Speed in Energy Demand Prediction - Experience Report from an R &D project. DEXA (1) Witold Andrzejewski, Jedrzej Potoniec, Maciej Drozdowski, Jerzy Stefanowski, Robert Wrembel, Pawel Stapf
2022	J	`jnl`	Quality versus speed in energy demand prediction for district heating systems. CoRR Witold Andrzejewski, Jedrzej Potoniec, Maciej Drozdowski, Jerzy Stefanowski, Robert Wrembel, Pawel Stapf
2022	J	`jnl`	The Influence of Multiple Classes on Learning Online Classifiers from Imbalanced and Concept Drifting Data Streams. CoRR Agnieszka Lipska, Jerzy Stefanowski
2022	—	`conf`	The Influence of Multiple Classes on Learning from Imbalanced Data Streams. LIDTA Agnieszka Lipska, Jerzy Stefanowski
2022	J	`jnl`	What makes multi-class imbalanced problems difficult? An experimental study. Expert Syst. Appl. Mateusz Lango, Jerzy Stefanowski
2021	—	`conf`	Classification of Multi-class Imbalanced Data: Data Difficulty Factors and Selected Methods for Improving Classifiers. IJCRS Jerzy Stefanowski
2021	—	`conf`	Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification. PKDD/ECML Workshops (1) Kamil Plucinski, Mateusz Lango, Jerzy Stefanowski
2021	J	`jnl`	The impact of data difficulty factors on classification of imbalanced and concept drifting data streams. Knowl. Inf. Syst. Dariusz Brzezinski, Leandro L. Minku, Tomasz Pewinski, Jerzy Stefanowski, Artur Szumaczuk
2021	—	`conf`	Time Aspect in Making an Actionable Prediction of a Conversation Breakdown. ECML/PKDD (5) Piotr Janiszewski, Mateusz Lango, Jerzy Stefanowski
2021	—	`conf`	Two Ways of Extending BRACID Rule-based Classifiers for Multi-class Imbalanced Data. LIDTA@ECML/PKDD Maria Naklicka, Jerzy Stefanowski
2020	J	`jnl`	On the Dynamics of Classification Measures for Imbalanced and Streaming Data. IEEE Trans. Neural Networks Learn. Syst. Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
2020	—	`conf`	multi-imbalance: Open Source Python Toolbox for Multi-class Imbalanced Classification. ECML/PKDD (5) Jacek Grycza, Damian Horna, Hanna Klimczak, Mateusz Lango, Kamil Plucinski, Jerzy Stefanowski
2019	—	`ed.`	Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems - AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019, Revised Selected Papers KR4HC/ProHealth/TEAAM@AIME Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic
2019	J	`jnl`	Using Information on Class Interrelations to Improve Classification of Multiclass Imbalanced Data: A New Resampling Algorithm. Int. J. Appl. Math. Comput. Sci. Malgorzata Janicka, Mateusz Lango, Jerzy Stefanowski
2018	—	`conf`	ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information. LIDTA@ECML/PKDD Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski
2018	—	`ch.`	Improving Bagging Ensembles for Class Imbalanced Data by Active Learning. Advances in Feature Selection for Data and Pattern Recognition Jerzy Blaszczynski, Jerzy Stefanowski
2018	—	`conf`	Local Data Characteristics in Learning Classifiers from Imbalanced Data. Advances in Data Analysis with Computational Intelligence Methods Jerzy Blaszczynski, Jerzy Stefanowski
2018	J	`jnl`	Multi-class and feature selection extensions of Roughly Balanced Bagging for imbalanced data. J. Intell. Inf. Syst. Mateusz Lango, Jerzy Stefanowski
2018	J	`jnl`	Visual-based analysis of classification measures and their properties for class imbalanced problems. Inf. Sci. Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
2017	C	`conf`	Actively Balanced Bagging for Imbalanced Data. ISMIS Jerzy Blaszczynski, Jerzy Stefanowski
2017	—	`conf`	An Algorithm for Selective Preprocessing of Multi-class Imbalanced Data. CORES Szymon Wojciechowski, Szymon Wilk, Jerzy Stefanowski
2017	B	`conf`	Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data. DS Mateusz Lango, Dariusz Brzezinski, Sebastian Firlik, Jerzy Stefanowski
2017	J	`jnl`	Ensemble learning for data stream analysis: A survey. Inf. Fusion Bartosz Krawczyk, Leandro L. Minku, João Gama, Jerzy Stefanowski, Michal Wozniak
2017	C	`conf`	Evaluating Difficulty of Multi-class Imbalanced Data. ISMIS Mateusz Lango, Krystyna Napierala, Jerzy Stefanowski
2017	J	`jnl`	Exploring complex and big data. Int. J. Appl. Math. Comput. Sci. Jerzy Stefanowski, Krzysztof Krawiec, Robert Wrembel
2017	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III ECML/PKDD (3) Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Zitnik, Michelangelo Ceci, Saso Dzeroski
2017	J	`jnl`	Prequential AUC: properties of the area under the ROC curve for data streams with concept drift. Knowl. Inf. Syst. Dariusz Brzezinski, Jerzy Stefanowski
2017	—	`ch.`	Stream Classification. Encyclopedia of Machine Learning and Data Mining Jerzy Stefanowski, Dariusz Brzezinski
2017	—	`conf`	Tetrahedron: Barycentric Measure Visualizer. ECML/PKDD (3) Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
2017	J	`jnl`	Visual-Based Analysis of Classification Measures with Applications to Imbalanced Data. CoRR Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
2016	—	`conf`	Application of Preprocessing Methods to Imbalanced Clinical Data: An Experimental Study. ITIB (1) Szymon Wilk, Jerzy Stefanowski, Szymon Wojciechowski, Ken J. Farion, Wojtek Michalowski
2016	—	`conf`	Consistency Driven Feature Subspace Aggregating for Ordinal Classification. IJCRS Jerzy Blaszczynski, Jerzy Stefanowski, Roman Slowinski
2016	—	`ch.`	Dealing with Data Difficulty Factors While Learning from Imbalanced Data. Challenges in Computational Statistics and Data Mining Jerzy Stefanowski
2016	B	`conf`	Ensemble Diversity in Evolving Data Streams. DS Dariusz Brzezinski, Jerzy Stefanowski
2016	—	`conf`	Increasing the Interpretability of Rules Induced from Imbalanced Data by Using Bayesian Confirmation Measures. NFMCP@PKDD/ECML Krystyna Napierala, Jerzy Stefanowski, Izabela Szczech
2016	—	`conf`	PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis. SemEval@NAACL-HLT Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski
2016	J	`jnl`	Post-processing of BRACID Rules Induced from Imbalanced Data. Fundam. Informaticae Krystyna Napierala, Jerzy Stefanowski
2016	J	`jnl`	Types of minority class examples and their influence on learning classifiers from imbalanced data. J. Intell. Inf. Syst. Krystyna Napierala, Jerzy Stefanowski
2015	J	`jnl`	Abstaining in rule set bagging for imbalanced data. Log. J. IGPL Krystyna Napierala, Jerzy Stefanowski
2015	—	`conf`	Adaptive Ensembles for Evolving Data Streams - Combining Block-Based and Online Solutions. NFMCP Jerzy Stefanowski
2015	J	`jnl`	Addressing imbalanced data with argument based rule learning. Expert Syst. Appl. Krystyna Napierala, Jerzy Stefanowski
2015	J	`jnl`	Data stream classification and big data analytics. Neurocomputing Bartosz Krawczyk, Jerzy Stefanowski, Michal Wozniak
2015	J	`jnl`	Neighbourhood sampling in bagging for imbalanced data. Neurocomputing Jerzy Blaszczynski, Jerzy Stefanowski
2015	—	`conf`	On Properties of Undersampling Bagging and Its Extensions for Imbalanced Data. CORES Jerzy Stefanowski
2015	J	`jnl`	SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering. Inf. Sci. José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
2015	—	`conf`	The Usefulness of Roughly Balanced Bagging for Complex and High-Dimensional Imbalanced Data. NFMCP Mateusz Lango, Jerzy Stefanowski
2014	J	`jnl`	Combining block-based and online methods in learning ensembles from concept drifting data streams. Inf. Sci. Dariusz Brzezinski, Jerzy Stefanowski
2014	C	`conf`	Local Characteristics of Minority Examples in Pre-processing of Imbalanced Data. ISMIS Jerzy Stefanowski, Krystyna Napierala, Malgorzata Trzcielinska
2014	C	`conf`	Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering. IDEAL José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
2014	J	`jnl`	Open challenges for data stream mining research. SIGKDD Explor. Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski
2014	—	`conf`	Prequential AUC for Classifier Evaluation and Drift Detection in Evolving Data Streams. NFMCP Dariusz Brzezinski, Jerzy Stefanowski
2014	J	`jnl`	Processing and mining complex data streams. Inf. Sci. Jerzy Stefanowski, Alfredo Cuzzocrea, Dominik Slezak
2014	C	`conf`	RILL: Algorithm for Learning Rules from Streaming Data with Concept Drift. ISMIS Magdalena Deckert, Jerzy Stefanowski
2014	J	`jnl`	Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm. IEEE Trans. Neural Networks Learn. Syst. Dariusz Brzezinski, Jerzy Stefanowski
2014	—	`conf`	The Impact of Local Data Characteristics on Learning from Imbalanced Data. RSEISP Jerzy Stefanowski
2013	—	`conf`	Extending Bagging for Imbalanced Data. CORES Jerzy Blaszczynski, Jerzy Stefanowski, Lukasz Idkowiak
2012	J	`jnl`	BRACID: a comprehensive approach to learning rules from imbalanced data. J. Intell. Inf. Syst. Krystyna Napierala, Jerzy Stefanowski
2012	—	`conf`	Comparing Block Ensembles for Data Streams with Concept Drift. ADBIS Workshops Magdalena Deckert, Jerzy Stefanowski
2012	J	`jnl`	IIvotes ensemble for imbalanced data. Intell. Data Anal. Jerzy Blaszczynski, Magdalena Deckert, Jerzy Stefanowski, Szymon Wilk
2012	—	`conf`	Identification of Different Types of Minority Class Examples in Imbalanced Data. HAIS (2) Krystyna Napierala, Jerzy Stefanowski
2012	—	`conf`	Modifications of Classification Strategies in Rule Set Based Bagging for Imbalanced Data. HAIS (2) Krystyna Napierala, Jerzy Stefanowski
2011	—	`conf`	Accuracy Updated Ensemble for Data Streams with Concept Drift. HAIS (2) Dariusz Brzezinski, Jerzy Stefanowski
2011	C	`conf`	Local neighbourhood extension of SMOTE for mining imbalanced data. CIDM Tomasz Maciejewski, Jerzy Stefanowski
2010	—	`conf`	Argument Based Generalization of MODLEM Rule Induction Algorithm. RSCTC Krystyna Napierala, Jerzy Stefanowski
2010	—	`conf`	Integrating Selective Pre-processing of Imbalanced Data with Ivotes Ensemble. RSCTC Jerzy Blaszczynski, Magdalena Deckert, Jerzy Stefanowski, Szymon Wilk
2010	—	`conf`	Learning from Imbalanced Data in Presence of Noisy and Borderline Examples. RSCTC Krystyna Napierala, Jerzy Stefanowski, Szymon Wilk
2010	—	`conf`	Ordinal Classification with Monotonicity Constraints by Variable Consistency Bagging. RSCTC Jerzy Blaszczynski, Roman Slowinski, Jerzy Stefanowski
2010	J	`jnl`	Variable Consistency Bagging Ensembles. Trans. Rough Sets Jerzy Blaszczynski, Roman Slowinski, Jerzy Stefanowski
2009	J	`jnl`	An experimental evaluation of two approaches to mining context based sequential patterns. Control. Cybern. Jerzy Stefanowski, Radoslaw Z. Ziembinski
2009	C	`conf`	Ensembles of Abstaining Classifiers Based on Rule Sets. ISMIS Jerzy Blaszczynski, Jerzy Stefanowski, Magdalena Zajac
2008	B	`conf`	Selective Pre-processing of Imbalanced Data for Improving Classification Performance. DaWaK Jerzy Stefanowski, Szymon Wilk
2007	—	`conf`	Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles. RSEISP Jerzy Stefanowski
2007	—	`conf`	Comprehensible and Accurate Cluster Labels in Text Clustering. RIAO Jerzy Stefanowski, Dawid Weiss
2007	—	`conf`	Evaluating Importance of Conditions in the Set of Discovered Rules. RSFDGrC Salvatore Greco, Roman Slowinski, Jerzy Stefanowski
2007	J	`jnl`	On Combined Classifiers, Rule Induction and Rough Sets. Trans. Rough Sets Jerzy Stefanowski
2007	—	`ed.`	Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007, Proceedings RSFDGrC Aijun An, Jerzy Stefanowski, Sheela Ramanna, Cory J. Butz, Witold Pedrycz, Guoyin Wang
2006	J	`jnl`	An Empirical Study of Using Rule Induction and Rough Sets to Software Cost Estimation. Fundam. Informaticae Jerzy Stefanowski
2006	C	`conf`	Classification of Polish Email Messages: Experiments with Various Data Representations. ISMIS Jerzy Stefanowski, Marcin Zienkowicz
2006	J	`jnl`	Preface. Fundam. Informaticae Mariusz Flasinski, Edward Nawarecki, Lech Polkowski, Robert Schaefer, Jerzy Stefanowski, Zbigniew Suraj
2006	J	`jnl`	Rough Sets for Handling Imbalanced Data: Combining Filtering and Rule-based Classifiers. Fundam. Informaticae Jerzy Stefanowski, Szymon Wilk
2005	J	`jnl`	A Comparison of Two Approaches to Data Mining from Imbalanced Data. J. Intell. Manuf. Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon Wilk
2005	—	`conf`	Mining Context Based Sequential Patterns. AWIC Jerzy Stefanowski, Radoslaw Z. Ziembinski
2005	C	`conf`	On Using Rule Induction in Multiple Classifiers with a Combiner Aggregation Strategy. ISDA Jerzy Stefanowski, Slawomir Nowaczyk
2004	B	`conf`	A Comparison of Two Approaches to Data Mining from Imbalanced Data. KES Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon Wilk
2004	J	`jnl`	An experimental evaluation of improving rule based classifiers with two approaches that change representations of learning examples. Eng. Appl. Artif. Intell. Jerzy Stefanowski
2004	J	`jnl`	Hyperplane Aggregation of Dominance Decision Rules. Fundam. Informaticae Roman Pindur, Robert Susmaga, Jerzy Stefanowski
2004	J	`jnl`	Incremental versus Non-incremental Rule Induction for Multicriteria Classification. Trans. Rough Sets Salvatore Greco, Roman Slowinski, Jerzy Stefanowski, Marcin Zurawski
2004	—	`conf`	Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition. Intelligent Information Systems Stanislaw Osinski, Jerzy Stefanowski, Dawid Weiss
2004	J	`jnl`	Rough Set Theory and Decision Rules in Data Analysis of Breast Cancer Patients. Trans. Rough Sets Jerzy Zaluski, Renata Szoszkiewicz, Jerzy Krysinski, Jerzy Stefanowski
2004	—	`conf`	The Bagging and n Rough Sets and Current Trends in Computing Jerzy Stefanowski
2003	—	`conf`	Carrot and Language Properties in Web Search Results Clustering. AWIC Jerzy Stefanowski, Dawid Weiss
2003	—	`conf`	Incremental Rule Induction for Multicriteria and Multiattribute Classification. IIS Jerzy Stefanowski, Marcin Zurawski
2003	—	`conf`	Web Search Results Clustering in Polish: Experimental Evaluation of Carrot. IIS Dawid Weiss, Jerzy Stefanowski
2002	J	`jnl`	Application of Rule Induction and Rough Sets to Verification of Magnetic Resonance Diagnosis. Fundam. Informaticae Krzysztof Slowinski, Jerzy Stefanowski, Dariusz Siwinski
2002	—	`conf`	Bagging and Induction of Decision Rules. Intelligent Information Systems Jerzy Stefanowski
2002	—	`conf`	Importance and Interaction of Conditions in Decision Rules. Rough Sets and Current Trends in Computing Salvatore Greco, Benedetto Matarazzo, Roman Slowinski, Jerzy Stefanowski
2002	—	`conf`	Induction of Decision Rules and Classification in the Valued Tolerance Approach. Rough Sets and Current Trends in Computing Jerzy Stefanowski, Alexis Tsoukiàs
2002	C	`conf`	Mining Association Rules in Preference-Ordered Data. ISMIS Salvatore Greco, Roman Slowinski, Jerzy Stefanowski
2001	J	`jnl`	Evaluating business credit risk by means of approach-integrating decision rules and case-based learning. Intell. Syst. Account. Finance Manag. Jerzy Stefanowski, Szymon Wilk
2001	J	`jnl`	Incomplete Information Tables and Rough Classification. Comput. Intell. Jerzy Stefanowski, Alexis Tsoukiàs
2001	J	`jnl`	Induction of decision rules in classification and discovery-oriented perspectives. Int. J. Intell. Syst. Jerzy Stefanowski, Daniel Vanderpooten
2001	J	`jnl`	Three discretization methods for rule induction. Int. J. Intell. Syst. Jerzy W. Grzymala-Busse, Jerzy Stefanowski
2000	—	`conf`	An Algorithm for Induction of Decision Rules Consistent with the Dominance Principle. Rough Sets and Current Trends in Computing Salvatore Greco, Benedetto Matarazzo, Roman Slowinski, Jerzy Stefanowski
2000	—	`conf`	Valued Tolerance and Decision Rules. Rough Sets and Current Trends in Computing Jerzy Stefanowski, Alexis Tsoukiàs
2000	—	`conf`	Variable Consistency Model of Dominance-Based Rough Sets Approach. Rough Sets and Current Trends in Computing Salvatore Greco, Benedetto Matarazzo, Roman Slowinski, Jerzy Stefanowski
1999	—	`conf`	On the Extension of Rough Sets under Incomplete Information. RSFDGrC Jerzy Stefanowski, Alexis Tsoukiàs
1998	—	`conf`	Experiments on Solving Multiclass Learning Problems by ECML Jacek Jelonek, Jerzy Stefanowski
1998	—	`conf`	Handling Continuous Attributes in Discovery of Strong Decision Rules. Rough Sets and Current Trends in Computing Jerzy Stefanowski
1998	—	`conf`	ROSE - Software Implementation of the Rough Set Theory. Rough Sets and Current Trends in Computing Bartlomiej Predki, Roman Slowinski, Jerzy Stefanowski, Robert Susmaga, Szymon Wilk
1997	J	`jnl`	Feature subset selection for classification of histological images. Artif. Intell. Medicine Jacek Jelonek, Jerzy Stefanowski
1997	—	`conf`	Rough Set Theory and Rule Induction Techniques for Discovery of Attribute Dependencies in Medical Information Systems. PKDD Jerzy Stefanowski, Krzysztof Slowinski
1996	J	`jnl`	Rough Sets: Facts Versus Misconceptions. Informatica (Slovenia) Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Wojciech Ziarko
1996	J	`jnl`	Rough-Set Reasoning about Uncertain Data. Fundam. Informaticae Roman Slowinski, Jerzy Stefanowski
1993	—	`conf`	A General Two-Stage Approach to Inducing Rules from Examples. RSKD Jerzy Stefanowski, Daniel Vanderpooten
1993	—	`conf`	Handling Various Types of Uncertainty in the Rough Set Approach. RSKD Roman Slowinski, Jerzy Stefanowski
1993	—	`conf`	Neural Networks and Rough Sets - Comparison and Combination for Classification of Histological Pictures. RSKD Jacek Jelonek, Krzysztof Krawiec, Roman Slowinski, Jerzy Stefanowski, Janusz Szymas
1992	—	`ch.`	'Roughdas' and 'Roughclass' Software Implementations of the Rough Sets Approach. Intelligent Decision Support Roman Slowinski, Jerzy Stefanowski
1992	—	`ch.`	Analysis of Diagnostic Symptoms in Vibroacoustic Diagnostics by Means of the Rough Sets Theory. Intelligent Decision Support Ryszard Nowicki, Roman Slowinski, Jerzy Stefanowski
1992	—	`ch.`	Comparison of the Rough Sets Approach and Probabilistic Data Analysis Techniques on a Common Set of Medical Data. Intelligent Decision Support Ewa Krusinska, Ankica Babic, Roman Slowinski, Jerzy Stefanowski
1992	C	`conf`	The Rough Sets Approach to Knowledge Analysis for Classification Support in Technical Diagnostics of Mechanical Objects. IEA/AIE Jerzy Stefanowski, Roman Slowinski, Ryszard Nowicki