Rough sets: Some extensions
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[1] Hans C. van Houwelingen,et al. The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Trevor Hastie, Robert Tibshirani and Jerome Friedman, Springer, New York, 2001. No. of pages: xvi+533. ISBN 0‐387‐95284‐5 , 2004 .
[2] Lotfi A. Zadeh,et al. A New Direction in AI: Toward a Computational Theory of Perceptions , 2001, AI Mag..
[3] Ning Zhong,et al. Intelligent Technologies for Information Analysis , 2004, Springer Berlin Heidelberg.
[4] Lech Polkowski,et al. Rough Mereology: A Rough Set Paradigm for Unifying Rough Set Theory and Fuzzy Set Theory , 2003, Fundam. Informaticae.
[5] G. Mann. The Quark and the Jaguar: adventures in the simple and the complex , 1994 .
[6] Andrzej Skowron,et al. Rough mereology: A new paradigm for approximate reasoning , 1996, Int. J. Approx. Reason..
[7] Stephen Read,et al. Thinking about logic : an introduction to the philosophy oflogic , 1995 .
[8] Andrzej Skowron,et al. Rough Sets and Vague Concepts , 2004, Fundam. Informaticae.
[9] James J. Alpigini,et al. Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing , 2002 .
[10] L. Barsalou,et al. Whither structured representation? , 1999, Behavioral and Brain Sciences.
[11] James F. Peters,et al. Rough Sets: Trends and Challenges , 2003, RSFDGrC.
[12] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[13] Jerzy Stefanowski,et al. Hyperplane Aggregation of Dominance Decision Rules , 2003, Fundam. Informaticae.
[14] Steffen Staab,et al. Handbook on Ontologies (International Handbooks on Information Systems) , 2004 .
[15] Ivo Düntsch,et al. Rough set data analysis: A road to non-invasive knowledge discovery , 2000 .
[16] Andrzej Skowron,et al. Rough mereology in information systems. A case study: qualitative spatial reasoning , 2000 .
[17] Andrzej Skowron,et al. Rudiments of rough sets , 2007, Inf. Sci..
[18] Andrzej Skowron,et al. Approximation Spaces and Information Granulation , 2004, Trans. Rough Sets.
[19] Salvatore Greco,et al. Incremental versus Non-incremental Rule Induction for Multicriteria Classification , 2004, Trans. Rough Sets.
[20] Leo Breiman,et al. Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001 .
[21] Yiyu Yao,et al. On Generalizing Rough Set Theory , 2003, RSFDGrC.
[22] D. Vanderpooten. Similarity Relation as a Basis for Rough Approximations , 1995 .
[23] Masahiro Inuiguchi,et al. Transactions on Rough Sets II: Rough Sets and Fuzzy Sets (Lecture Notes in Computer Science) , 2005 .
[24] Andrzej Skowron,et al. Rough-Neural Computing: Techniques for Computing with Words , 2004, Cognitive Technologies.
[25] J. Sutherland. The Quark and the Jaguar , 1994 .
[26] J. Stepaniuk. Approximation Spaces, Reducts and Representatives , 1998 .
[27] G. Leibniz. Discourse on Metaphysics , 1902 .
[28] Dominik Slezak,et al. Feedforward Concept Networks , 2004, MSRAS.
[29] William K. Bellinger. Decision Rules , 2008, Encyclopedia of GIS.
[30] Andrzej Skowron,et al. Rough Mereological Calculi of Granules: A Rough Set Approach To Computation , 2001, Comput. Intell..
[31] Leo Breiman,et al. Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001, Statistical Science.
[32] Rajkumar Roy,et al. Advances in Soft Computing , 2018, Lecture Notes in Computer Science.
[33] Yiyu Yao,et al. Information granulation and rough set approximation , 2001, Int. J. Intell. Syst..
[34] Andrzej Skowron,et al. Toward Intelligent Systems: Calculi of Information Granules , 2001, JSAI Workshops.
[35] Andrzej Skowron,et al. Rough set approach to pattern extraction from classifiers, In: Proceedings of the Workshop on Rough Sets in Knowledge Discovery and Soft Computing at ETAPS’2003 , 2003 .
[36] Z. Pawlak. Classification of objects by means of attributes , 1981 .
[37] T. Poggio,et al. The Mathematics of Learning: Dealing with Data , 2005, 2005 International Conference on Neural Networks and Brain.
[38] E. H. Moore. ON THE FOUNDATIONS OF MATHEMATICS. , 1903 .
[39] Roman Słowiński,et al. Dealing with Missing Data in Rough Set Analysis of Multi-Attribute and Multi-Criteria Decision Problems , 2000 .
[41] Jerzy W. Grzymala-Busse,et al. Transactions on Rough Sets XII , 2010, Lecture Notes in Computer Science.
[42] Steffen Staab,et al. International Handbooks on Information Systems , 2013 .
[43] Jan G. Bazan. Behavioral Pattern Identification Through Rough Set Modeling , 2005, Fundam. Informaticae.
[44] B. C. Brookes,et al. Information Sciences , 2020, Cognitive Skills You Need for the 21st Century.
[45] Andrzej Skowron,et al. Approximate Reasoning in Distributed Environments , 2004 .
[46] Salvatore Greco,et al. Rough sets theory for multicriteria decision analysis , 2001, Eur. J. Oper. Res..
[47] Andrzej Skowron,et al. Ontological Framework for Approximation , 2005, RSFDGrC.
[48] Philosophical Essays , 1997, Nature.
[49] Tsau Young Lin,et al. A Review of Rough Set Models , 1997 .
[50] C. A. Murthy,et al. Proceedings of the First international conference on Pattern Recognition and Machine Intelligence , 2005 .
[51] J. Grzymala-Busse. Managing uncertainty in expert systems , 1991 .
[52] S. Poirier. Foundations of mathematics , 2007 .
[53] Andrzej Skowron,et al. Rough sets: Trends and challenges (plenary talk) , 2003 .
[54] Peter Stone,et al. Layered learning in multiagent systems - a winning approach to robotic soccer , 2000, Intelligent robotics and autonomous agents.
[55] Dominik Slezak,et al. Normalized Decision Functions and Measures for Inconsistent Decision Tables Analysis , 2000, Fundam. Informaticae.
[56] Janusz Kacprzyk,et al. Computing with Words in Information/Intelligent Systems 1 , 1999 .
[57] Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .
[58] Andrzej Skowron,et al. Information granules: Towards foundations of granular computing , 2001, Int. J. Intell. Syst..
[59] Andrzej Skowron,et al. Layered Learning for Concept Synthesis , 2004, Trans. Rough Sets.
[60] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[61] Patrick Brézillon,et al. Lecture Notes in Artificial Intelligence , 1999 .
[62] D. Scott. Perceptual learning. , 1974, Queen's nursing journal.
[63] Wojciech Ziarko,et al. Variable Precision Rough Set Model , 1993, J. Comput. Syst. Sci..
[64] F. Ramsey. The foundations of mathematics , 1932 .
[65] Georgios I. Doukidis,et al. Decision making : recent developments and worldwide applications , 2000 .
[66] Andrzej Skowron,et al. Rough sets in perception-based computing (keynote talk) , 2005 .
[67] Dominik Slezak,et al. The investigation of the Bayesian rough set model , 2005, Int. J. Approx. Reason..
[68] Wojciech Ziarko,et al. The Discovery, Analysis, and Representation of Data Dependencies in Databases , 1991, Knowledge Discovery in Databases.
[69] S. Greco,et al. Data mining tasks and methods: Classification: multicriteria classification , 2002 .
[70] S. Harnad. Categorical Perception: The Groundwork of Cognition , 1990 .
[71] Dominik Slezak,et al. Rough Sets and Bayes Factor , 2005, Trans. Rough Sets.
[72] S. Greco,et al. Dominance-Based Rough Set Approach to Knowledge Discovery (II): Extensions and Applications , 2004 .
[73] Hung Son Nguyen,et al. A View on Rough Set Concept Approximations , 2003, Fundam. Informaticae.
[74] Sven Behnke,et al. Hierarchical Neural Networks for Image Interpretation , 2003, Lecture Notes in Computer Science.
[75] Salvatore Greco,et al. Rough Set Analysis of Preference-Ordered Data , 2002, Rough Sets and Current Trends in Computing.
[76] R. Keefe. Theories of vagueness , 2000 .
[77] Andrzej Skowron,et al. Tolerance Approximation Spaces , 1996, Fundam. Informaticae.
[78] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[79] Andrzej Skowron,et al. Perception logic in intelligent systems (keynote talk) , 2005 .
[80] Lech Polkowski,et al. Rough Sets in Knowledge Discovery 2 , 1998 .
[81] Tuan Trung Nguyen,et al. Rough Set Approach to Domain Knowledge Approximation , 2003, Fundam. Informaticae.
[82] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[83] James F. Peters,et al. Rough Set Approach to Pattern Extraction from Classifiers , 2003, RSKD.
[84] S. Leśniewski. Grundzüge eines neuen Systems der Grundlagen der Mathematik , 1929 .
[85] Solomon Marcus,et al. The Paradox of the Heap of Grains in Respect to Roughness, Fuzziness and Negligibility , 1998, Rough Sets and Current Trends in Computing.
[86] Jan G. Bazan,et al. Rough set algorithms in classification problem , 2000 .
[87] Dominik Ślęzak,et al. Various approaches to reasoning with frequency based decision reducts: a survey , 2000 .
[88] Sudarsan Nanda,et al. On rough relations , 1998 .
[89] A. Skowron,et al. Towards adaptive calculus of granules , 1998 .
[90] Munindar P. Singh,et al. Readings in agents , 1997 .
[91] Salvatore Greco,et al. Fuzzy Similarity Relation as a Basis for Rough Approximations , 1998, Rough Sets and Current Trends in Computing.
[92] Lech Polkowski,et al. Toward Rough Set Foundations. Mereological Approach , 2004, Rough Sets and Current Trends in Computing.
[93] Andrzej Skowron,et al. Complex Patterns , 2003, Fundam. Informaticae.
[94] Janusz Zalewski,et al. Rough sets: Theoretical aspects of reasoning about data , 1996 .
[95] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[96] Zdzislaw Pawlak,et al. Decision Rules, Bayes' Rule and Ruogh Sets , 1999, RSFDGrC.
[97] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[98] Andrzej Skowron,et al. Classifiers Based on Approximate Reasoning Schemes , 2004, MSRAS.
[99] S. Tsumoto,et al. Rough set methods and applications: new developments in knowledge discovery in information systems , 2000 .
[100] Andrzej Skowron,et al. Information Granules and Rough-Neural Computing , 2004 .
[101] Andrzej Skowron,et al. On-Line Elimination of Non-relevant Parts of Complex Objects in Behavioral Pattern Identification , 2005, PReMI.
[102] Andrzej Skowron,et al. Rough Sets and Higher Order Vagueness , 2005, RSFDGrC.
[103] Andrzej Skowron,et al. Monitoring, Security, and Rescue Techniques in Multiagent Systems (Advances in Soft Computing) , 2005 .
[104] S. Greco,et al. Dominance-Based Rough Set Approach to Knowledge Discovery (I): General Perspective , 2004 .