Jerzy W. Grzymala-Busse - researchr alias

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2011

Probabilistic rule induction with the LERS data mining systemJerzy W. Grzymala-Busse, Yiyu Yao. ijis, 26(6):518-539, 2011. [doi]

A Comparison of Some Rough Set Approaches to Mining Symbolic Data with Missing Attribute ValuesJerzy W. Grzymala-Busse. ismis 2011: 52-61 [doi]

Transactions on Rough Sets XIIIJames F. Peters, Andrzej Skowron, Chien-Chung Chan, Jerzy W. Grzymala-Busse, Wojciech Ziarko, editors, Volume 6499 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Preface: A rough set approach to data miningJames F. Peters, Chien-Chung Chan, Jerzy W. Grzymala-Busse, Wojciech Ziarko. ijis, 26(6):497-498, 2011. [doi]

2010

A Comparison of Three Voting Methods for Bagging with the MLEM2 AlgorithmClinton Cohagan, Jerzy W. Grzymala-Busse, Zdzislaw S. Hippe. ideal 2010: 118-125 [doi]

Mining Inconsistent Data with the Bagged MLEM2 Rule Induction AlgorithmClinton Cohagan, Jerzy W. Grzymala-Busse, Zdzislaw S. Hippe. grc 2010: 115-120 [doi]

Definability and Other Properties of Approximations for Generalized Indiscernibility RelationsJerzy W. Grzymala-Busse, Wojciech Rzasa. trs, 11:14-39, 2010. [doi]

A Local Version of the MLEM2 Algorithm for Rule InductionJerzy W. Grzymala-Busse, Wojciech Rzasa. FUIN, 100(1-4):99-116, 2010. [doi]

An Empirical Comparison of Rule Sets Induced by LERS and Probabilistic Rough ClassificationJerzy W. Grzymala-Busse, Shantan R. Marepally, Yiyu Yao. rsctc 2010: 590-599 [doi]

Increasing Incompleteness of Data Sets - A Strategy for Inducing Better Rule SetsJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse. In Jacek Koronacki, Zbigniew W. Ras, Slawomir T. Wierzchon, Janusz Kacprzyk, editors, Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S. Michalski. Volume 262 of Studies in Computational Intelligence, pages 345-365, Springer, 2010. [doi]

Selected Topics of Data MiningJerzy W. Grzymala-Busse. grc 2010: 22-23 [doi]

Sensitivity and Specificity for Mining Data with Increased IncompletenessJerzy W. Grzymala-Busse, Shantan R. Marepally. icaisc 2010: 355-362 [doi]

Mining Numerical Data - A Rough Set ApproachJerzy W. Grzymala-Busse. trs, 11:1-13, 2010. [doi]

2010 IEEE International Conference on Granular Computing, GrC 2010, San Jose, California, USA, 14-16 August 2010Xiaohua Hu, Tsau Young Lin, Vijay V. Raghavan, Jerzy W. Grzymala-Busse, Qing Liu, Andrei Z. Broder, editors, IEEE Computer Society, 2010.

2009

An Extended Comparison of Six Approaches to Discretization - A Rough Set ApproachPiotr Blajdo, Zdzislaw S. Hippe, Teresa Mroczek, Jerzy W. Grzymala-Busse, Maksymilian Knap, Lukasz Piatek. FUIN, 94(2):121-131, 2009. [doi]

Local ApproximationsJerzy W. Grzymala-Busse, Wojciech Rzasa. ideal 2009: 9-16 [doi]

A Multiple Scanning Strategy for Entropy Based DiscretizationJerzy W. Grzymala-Busse. ismis 2009: 25-34 [doi]

2008

A Comparison of Six Approaches to Discretization-A Rough Set PerspectivePiotr Blajdo, Jerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Maksymilian Knap, Teresa Mroczek, Lukasz Piatek. rskt 2008: 31-38 [doi]

Rough Sets and Current Trends in Computing, 6th International Conference, RSCTC 2008, Akron, OH, USA, October 23-25, 2008, ProceedingsChien-Chung Chan, Jerzy W. Grzymala-Busse, Wojciech Ziarko, editors, Volume 5306 of Lecture Notes in Computer Science, Springer, 2008.

Approximation Space and LEM2-like Algorithms for Computing Local CoveringsJerzy W. Grzymala-Busse, Wojciech Rzasa. FUIN, 85(1-4):205-217, 2008. [doi]

Inducing Better Rule Sets by Adding Missing Attribute ValuesJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse. rsctc 2008: 160-169 [doi]

A Comparison of the LERS Classification System and Rule Management in PRSMJerzy W. Grzymala-Busse, Yiyu Yao. rsctc 2008: 202-210 [doi]

MLEM2 Rule Induction Algorithms: With and Without Merging IntervalsJerzy W. Grzymala-Busse. In Tsau Young Lin, Ying Xie, Anita Wasilewska, Churn-Jung Liau, editors, Data Mining: Foundations and Practice. Volume 118 of Studies in Computational Intelligence, pages 153-164, Springer, 2008. [doi]

Local and Global Approximations for Incomplete DataJerzy W. Grzymala-Busse, Wojciech Rzasa. trs, 8:21-34, 2008. [doi]

Three Approaches to Missing Attribute Values: A Rough Set PerspectiveJerzy W. Grzymala-Busse. In Tsau Young Lin, Ying Xie, Anita Wasilewska, Churn-Jung Liau, editors, Data Mining: Foundations and Practice. Volume 118 of Studies in Computational Intelligence, pages 139-152, Springer, 2008. [doi]

Improving Quality of Rule Sets by Increasing Incompleteness of Data Sets - A Rough Set ApproachJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse. ICSOFT 2008: 241-248

Synthesis of Medical Images in the Domain of Melanocytic Skin LesionsZdzislaw S. Hippe, Jerzy W. Grzymala-Busse, Lukasz Piatek. In Ewa Pietka, Jacek Kawa, editors, Information Technologies in Biomedicine. Volume 47 of Advances in Soft Computing, pages 225-231, Springer, 2008. [doi]

Rough Sets and Knowledge Technology, Third International Conference, RSKT 2008, Chengdu, China, May 17-19, 2008. ProceedingsGuoyin Wang, Tian-rui Li, Jerzy W. Grzymala-Busse, Duoqian Miao, Andrzej Skowron, Yiyu Yao, editors, Volume 5009 of Lecture Notes in Computer Science, Springer, 2008.

2007

Mining Mass Spectrometry Database Search Results - A Rough Set ApproachJianwen Fang, Jerzy W. Grzymala-Busse. rseisp 2007: 340-349 [doi]

Predicting Penetration Across the Blood-Brain Barrier - A Rough Set ApproachJianwen Fang, Jerzy W. Grzymala-Busse. grc 2007: 231-236 [doi]

Definability of Approximations for a Generalization of the Indiscernibility RelationJerzy W. Grzymala-Busse, Wojciech Rzasa. foci 2007: 65-72 [doi]

Deriving Belief Networks and Belief Rules from Data: A Progress ReportJerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Teresa Mroczek. trs, 7:53-69, 2007. [doi]

Neonatal Infection Diagnosis Using Constructive Induction in Data MiningJerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Agnieszka Kordek, Teresa Mroczek, Wojciech Podraza. rsfdgrc 2007: 289-296 [doi]

A Comparison of Three Approximation Strategies for Incomplete Data SetsJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse, Zdzislaw S. Hippe, Wojciech Rzasa. grc 2007: 301-306 [doi]

Mining Numerical Data - A Rough Set ApproachJerzy W. Grzymala-Busse. rseisp 2007: 12-21 [doi]

An Experimental Comparison of Three Rough Set Approaches to Missing Attribute ValuesJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse. trs, 6:31-50, 2007. [doi]

Transactions on Rough Sets VI, Commemorating the Life and Work of Zdzislaw Pawlak, Part IJames F. Peters, Andrzej Skowron, Ivo Düntsch, Jerzy W. Grzymala-Busse, Ewa Orlowska, Lech Polkowski, editors, Volume 4374 of Lecture Notes in Computer Science, Springer, 2007.

2006

Mining of MicroRNA Expression Data - A Rough Set ApproachJianwen Fang, Jerzy W. Grzymala-Busse. rskt 2006: 758-765 [doi]

Leukemia Prediction from Gene Expression Data-A Rough Set ApproachJianwen Fang, Jerzy W. Grzymala-Busse. icaisc 2006: 899-908 [doi]

A comparison of two partial matching strategies for classification of unseen casesJerzy W. Grzymala-Busse, Gustavo P. Sudre. grc 2006: 800-805 [doi]

Rough Set Strategies to Data with Missing Attribute ValuesJerzy W. Grzymala-Busse. In Tsau Young Lin, Setsuo Ohsuga, Churn-Jung Liau, Xiaohua Hu, editors, Foundations and Novel Approaches in Data Mining. Volume 9 of Studies in Computational Intelligence, pages 197-212, Springer, 2006. [doi]

Local and Global Approximations for Incomplete DataJerzy W. Grzymala-Busse, Wojciech Rzasa. rsctc 2006: 244-253 [doi]

A Rough Set Approach to Data with Missing Attribute ValuesJerzy W. Grzymala-Busse. rskt 2006: 58-67 [doi]

2005

Handling Missing Attribute ValuesJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse. In Oded Maimon, Lior Rokach, editors, The Data Mining and Knowledge Discovery Handbook. pages 37-57, Springer, 2005.

Data Mining Analysis of Granular Bed Caking during Hop ExtractionJerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Teresa Mroczek, Edward Rój, Boleslaw Skowronski. isda 2005: 426-431 [doi]

Discriminant versus Strong Rule SetsJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse, Jay Hamilton. iis 2005: 67-76

Belief Rules vs. Decision Rules: A Preliminary Appraisal of the ProblemJerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Teresa Mroczek. iis 2005: 431-435

Rule InductionJerzy W. Grzymala-Busse. In Oded Maimon, Lior Rokach, editors, The Data Mining and Knowledge Discovery Handbook. pages 277-294, Springer, 2005.

LERS - A Data Mining SystemJerzy W. Grzymala-Busse. In Oded Maimon, Lior Rokach, editors, The Data Mining and Knowledge Discovery Handbook. pages 1347-1351, Springer, 2005.

Handling Missing Attribute Values in Preterm Birth Data SetsJerzy W. Grzymala-Busse, Linda K. Goodwin, Witold J. Grzymala-Busse, Xinqun Zheng. rsfdgrc 2005: 342-351 [doi]

Incomplete Data and Generalization of Indiscernibility Relation, Definability, and ApproximationsJerzy W. Grzymala-Busse. rsfdgrc 2005: 244-253 [doi]

Data Mining Experiments on Hop Processing DataJerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Teresa Mroczek, Edward Rój, Boleslaw Skowronski. his 2005: 175-180 [doi]

Data Mining Methods Supporting Diagnosis of MelanomaJerzy W. Grzymala-Busse, Zdzislaw S. Hippe. cbms 2005: 371-373 [doi]

Infoscience technology: the impact of internet accessible melanoid data on health issuesJerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Maksymilian Knap, Wieslaw Paja. datascience, 4:77-81, 2005. [doi]

Characteristic Relations for Incomplete Data: A Generalization of the Indiscernibility RelationJerzy W. Grzymala-Busse. trs, :58-68, 2005. [doi]

Classification of Medical Images in the Domain of Melanoid Skin LesionsZdzislaw S. Hippe, Jerzy W. Grzymala-Busse, Piotr Blajdo, Maksymilian Knap, Teresa Mroczek, Wieslaw Paja, Mariusz Wrzesien. cores 2005: 519-526 [doi]

2004

Optimization of the ABCD Formula for Melanoma Diagnosis Using C4.5, a Data Mining SystemRon Andrews, Stanislaw Bajcar, Jerzy W. Grzymala-Busse, Zdzislaw S. Hippe, Chris Whiteley. rsctc 2004: 630-636 [doi]

Characteristic Relations for Incomplete Data: A Generalization of the Indiscernibility RelationJerzy W. Grzymala-Busse. rsctc 2004: 244-253 [doi]

Diagnosis of Melanoma Using IRIM, a Data Mining SystemJerzy W. Grzymala-Busse, Jay Hamilton, Zdzislaw S. Hippe. icaisc 2004: 996-1001 [doi]

Three Strategies to Rule Induction from Data with Numerical AttributesJerzy W. Grzymala-Busse. trs, :54-62, 2004. [doi]

Data with Missing Attribute Values: Generalization of Indiscernibility Relation and Rule InductionJerzy W. Grzymala-Busse. trs, :78-95, 2004. [doi]

A Comparison of Two Approaches to Data Mining from Imbalanced DataJerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon Wilk. kes 2004: 757-763 [doi]

Rough Set Approach to Incomplete DataJerzy W. Grzymala-Busse. icaisc 2004: 50-55 [doi]

Rules from Belief Networks: A Rough Set ApproachTeresa Mroczek, Jerzy W. Grzymala-Busse, Zdzislaw S. Hippe. rsctc 2004: 483-487 [doi]

Transactions on Rough Sets IIJames F. Peters, Andrzej Skowron, Didier Dubois, Jerzy W. Grzymala-Busse, Masahiro Inuiguchi, Lech Polkowski, editors, Volume 3135 of Lecture Notes in Computer Science, Springer, 2004.

Transactions on Rough Sets IJames F. Peters, Andrzej Skowron, Jerzy W. Grzymala-Busse, Bozena Kostek, Roman W. Swiniarski, Marcin S. Szczuka, editors, Volume 3100 of Lecture Notes in Computer Science, Springer, 2004.

Rough Sets and Current Trends in Computing, 4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004, ProceedingsShusaku Tsumoto, Roman Slowinski, Henryk Jan Komorowski, Jerzy W. Grzymala-Busse, editors, Volume 3066 of Lecture Notes in Computer Science, Springer, 2004.

2003

Optimization of the ABCD Formula Used for Melanoma DiagnosisAlison Alvarez, Stanislaw Bajcar, Frank M. Brown, Jerzy W. Grzymala-Busse, Zdzislaw S. Hippe. iis 2003: 233-240

Diagnosis of Melanoma Based on Data Mining and ABCD FormularsStanislaw Bajcar, Jerzy W. Grzymala-Busse, Witold J. Grzymala-Busse, Zdzislaw S. Hippe. his 2003: 614-622

Functional Behavioral Assessment Using the LERS Data Mining System - Strategies for Understanding Complex Physiological and Behavioral PatternsRachel L. Freeman, Jerzy W. Grzymala-Busse, Mark Harvey. jiis, 21(2):173-181, 2003.

Increasing sensitivity of preterm birth by changing rule strengthsJerzy W. Grzymala-Busse, Linda K. Goodwin, Xiaohui Zhang. prl, 24(6):903-910, 2003. [doi]

MLEM2 - Discretization During Rule InductionJerzy W. Grzymala-Busse. iis 2003: 499-508

A Comparison of Three Strategies to Rule Induction from Data with Numerical AttributesJerzy W. Grzymala-Busse. ENTCS, 82(4), 2003. [doi]

2002

2001

Analyzing the Relation between Heart Rate, Problem Behavior, and Environmental Events Using Data Mining System LERSRachel L. Freeman, Jerzy W. Grzymala-Busse, Laura A. Riffel, Stephen R. Schroeder. cbms 2001: 11-16 [doi]

Analysis of Self-Injurious Behavior by the LERS Data Mining SystemRachel L. Freeman, Jerzy W. Grzymala-Busse, Laura A. Riffel, Stephen R. Schroeder. jsai 2001: 395-399 [doi]

Melanoma Prediction Using k-Nearest Neighbor and LEM2 AlgorithmsJerzy W. Grzymala-Busse, Zdzislaw S. Hippe. iiswc 2001: 43-55

Three discretization methods for rule inductionJerzy W. Grzymala-Busse, Jerzy Stefanowski. ijis, 16(1):29-38, 2001.

Melanoma Prediction Using Data Mining System LERSJan P. Grzymala-Busse, Jerzy W. Grzymala-Busse, Zdzislaw S. Hippe. compsac 2001: 615-620 [doi]

Coping with Missing Attribute Values Based on Closest Fit in Preterm Birth Data: A Rough Set ApproachJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse, Linda K. Goodwin. ci, 17(3):425-434, 2001.

Using Rule Induction for Prediction of Self-Injuring Behavior in Animal Models of Development DisabilitiesPippa S. Loupe, Rachel L. Freeman, Jerzy W. Grzymala-Busse, Stephen R. Schroeder. cbms 2001: 171-176 [doi]

2000

A Comparison of Rule Matching Methods Used in AQ15 and LERSJerzy W. Grzymala-Busse, Pankaj Shah. ismis 2000: 148-156 [doi]

Data Mining Experiments with the Melanoma Data SetJerzy W. Grzymala-Busse, Zdzislaw S. Hippe. iiswc 2000: 27-34

Data Mining and Rough Set TheoryJerzy W. Grzymala-Busse, Wojciech Ziarko. CACM, 43(4):108-109, 2000. [doi]

A Comparison of Several Approaches to Missing Attribute Values in Data MiningJerzy W. Grzymala-Busse, Ming Hu. rsctc 2001: 378-385 [doi]

1999

Preterm Birth Risk Assessed by a New Method of Classifikation Using Selective Partial MatchingJerzy W. Grzymala-Busse, Linda K. Goodwin, Xiaohui Zhang. ismis 1999: 612-620

A Closest Fit Approach to Missing Attribute VAlues in Preterm Birth DataJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse, Linda K. Goodwin. rsfdgrc 1999: 405-413

1998

Classification Strategies Using Certain and Possible RulesJerzy W. Grzymala-Busse, Xihong Zou. rsctc 1998: 37-44 [doi]

Entropy of English Text: Experiments with Humans and a Machine Learning System Based on Rough SetsHamid Moradi, James A. Roberts, Jerzy W. Grzymala-Busse. isci, 104(1-2):31-47, 1998.

1997

Classification of Unseen Examples Under UncertaintyJerzy W. Grzymala-Busse. FUIN, 30(3/4):255-267, 1997.

A Machine Learning Experiment to Determine Part of Speech from Word-EndingsJerzy W. Grzymala-Busse, L. John Old. ismis 1997: 497-506

A New Version of the Rule Induction System LERSJerzy W. Grzymala-Busse. FUIN, 31(1):27-39, 1997.

1996

Global discretization of continuous attributes as preprocessing for machine learningMichal R. Chmielewski, Jerzy W. Grzymala-Busse. ijar, 15(4):319-331, 1996. [doi]

Rough Sets: Facts Versus MisconceptionsJerzy W. Grzymala-Busse, Jerzy Stefanowski, Wojciech Ziarko. informaticaSI, 20(4), 1996.

Partition Triples: A Tool for Reduction of Data SetsJerzy W. Grzymala-Busse, Soe Than. jcss, 53(3):575-582, 1996.

1995

The Usefulness of a Machine Learning Approach to Knowledge AcquisitionDobroslawa M. Grzymala-Busse, Jerzy W. Grzymala-Busse. ci, 11:268-279, 1995.

Rough SetsZdzislaw Pawlak, Jerzy W. Grzymala-Busse, Roman Slowinski, Wojciech Ziarko. CACM, 38(11):88-95, 1995.

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