Rough Sets And Data Mining
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Rough Sets And Data Mining
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Author : T.Y. Lin
language : en
Publisher: Springer
Release Date : 1996-11-30
Rough Sets And Data Mining written by T.Y. Lin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-11-30 with Computers categories.
Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters on the most recent developments in rough set theory and data mining. The chapters in this work cover a range of topics that focus on discovering dependencies among data, and reasoning about vague, uncertain and imprecise information. The authors of these chapters have been careful to include fundamental research with explanations as well as coverage of rough set tools that can be used for mining data bases. The contributing authors consist of some of the leading scholars in the fields of rough sets, data mining, machine learning and other areas of artificial intelligence. Among the list of contributors are Z. Pawlak, J Grzymala-Busse, K. Slowinski, and others. Rough Sets and Data Mining: Analysis of Imprecise Data will be a useful reference work for rough set researchers, data base designers and developers, and for researchers new to the areas of data mining and rough sets.
Data Mining Rough Sets And Granular Computing
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Author : Tsau Young Lin
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-04-10
Data Mining Rough Sets And Granular Computing written by Tsau Young Lin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04-10 with Computers categories.
During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing.
Rough Sets And Data Mining
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Author : T.Y. Lin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Rough Sets And Data Mining written by T.Y. Lin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters on the most recent developments in rough set theory and data mining. The chapters in this work cover a range of topics that focus on discovering dependencies among data, and reasoning about vague, uncertain and imprecise information. The authors of these chapters have been careful to include fundamental research with explanations as well as coverage of rough set tools that can be used for mining data bases. The contributing authors consist of some of the leading scholars in the fields of rough sets, data mining, machine learning and other areas of artificial intelligence. Among the list of contributors are Z. Pawlak, J Grzymala-Busse, K. Slowinski, and others. Rough Sets and Data Mining: Analysis of Imprecise Data will be a useful reference work for rough set researchers, data base designers and developers, and for researchers new to the areas of data mining and rough sets.
Rough Sets And Data Mining
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Author : T.Y. Lin
language : en
Publisher:
Release Date : 1996-11-30
Rough Sets And Data Mining written by T.Y. Lin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-11-30 with categories.
Rough Set Methods And Applications
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Author : Lech Polkowski
language : en
Publisher: Physica
Release Date : 2012-10-07
Rough Set Methods And Applications written by Lech Polkowski and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-07 with Computers categories.
Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research.
Rough Sets Fuzzy Sets Data Mining And Granular Computing
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Author : Guoyin Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-05-08
Rough Sets Fuzzy Sets Data Mining And Granular Computing written by Guoyin Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-08 with Computers categories.
This book constitutes the refereed proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2003, held in Chongqing, China in May 2003. The 39 revised full papers and 75 revised short papers presented together with 2 invited keynote papers and 11 invited plenary papers were carefully reviewed and selected from a total of 245 submissions. The papers are organized in topical sections on rough sets foundations and methods; fuzzy sets and systems; granular computing; neural networks and evolutionary computing; data mining, machine learning, and pattern recognition; logics and reasoning; multi-agent systems; and Web intelligence and intelligent systems.
Understanding And Using Rough Set Based Feature Selection Concepts Techniques And Applications
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Author : Muhammad Summair Raza
language : en
Publisher: Springer
Release Date : 2017-06-28
Understanding And Using Rough Set Based Feature Selection Concepts Techniques And Applications written by Muhammad Summair Raza and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-28 with Computers categories.
The book will provide: 1) In depth explanation of rough set theory along with examples of the concepts. 2) Detailed discussion on idea of feature selection. 3) Details of various representative and state of the art feature selection techniques along with algorithmic explanations. 4) Critical review of state of the art rough set based feature selection methods covering strength and weaknesses of each. 5) In depth investigation of various application areas using rough set based feature selection. 6) Complete Library of Rough Set APIs along with complexity analysis and detailed manual of using APIs 7) Program files of various representative Feature Selection algorithms along with explanation of each. The book will be a complete and self-sufficient source both for primary and secondary audience. Starting from basic concepts to state-of-the art implementation, it will be a constant source of help both for practitioners and researchers. Book will provide in-depth explanation of concepts supplemented with working examples to help in practical implementation. As far as practical implementation is concerned, the researcher/practitioner can fully concentrate on his/her own work without any concern towards implementation of basic RST functionality. Providing complexity analysis along with full working programs will further simplify analysis and comparison of algorithms.
Rough Sets Fuzzy Sets Data Mining And Granular Computing
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Author : Yiyu Yao
language : en
Publisher: Springer
Release Date : 2015-11-21
Rough Sets Fuzzy Sets Data Mining And Granular Computing written by Yiyu Yao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-21 with Computers categories.
This book constitutes the refereed conference proceedings of the 15th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2015, held in Tianjin, China in November 2015 as one of the co-located conference of the 2015 Joint Rough Set Symposium, JRS 2015. The 44 papers were carefully reviewed and selected from 97 submissions. The papers in this volume cover topics such as rough sets: the experts speak; generalized rough sets; rough sets and graphs; rough and fuzzy hybridization; granular computing; data mining and machine learning; three-way decisions; IJCRS 2015 data challenge.
Rough Sets
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Author : Z. Pawlak
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Rough Sets written by Z. Pawlak and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
To-date computers are supposed to store and exploit knowledge. At least that is one of the aims of research fields such as Artificial Intelligence and Information Systems. However, the problem is to understand what knowledge means, to find ways of representing knowledge, and to specify automated machineries that can extract useful information from stored knowledge. Knowledge is something people have in their mind, and which they can express through natural language. Knowl edge is acquired not only from books, but also from observations made during experiments; in other words, from data. Changing data into knowledge is not a straightforward task. A set of data is generally disorganized, contains useless details, although it can be incomplete. Knowledge is just the opposite: organized (e.g. laying bare dependencies, or classifications), but expressed by means of a poorer language, i.e. pervaded by imprecision or even vagueness, and assuming a level of granularity. One may say that knowledge is summarized and organized data - at least the kind of knowledge that computers can store.
Rough Sets Fuzzy Sets Data Mining And Granular Computing
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Author : Dominik Ślęzak
language : en
Publisher: Springer Science & Business Media
Release Date : 2005
Rough Sets Fuzzy Sets Data Mining And Granular Computing written by Dominik Ślęzak and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Artificial intelligence categories.
This volume contains the papers selected for presentation at the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st–September 3rd, 2005.