Rough Set Based Classification Systems

Author : Robert K. Nowicki
Publisher : Springer
ISBN 13 : 3030038955
Total Pages : 188 pages
Book Rating : 4.53/5 ( download)

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Download or read book Rough Set–Based Classification Systems written by Robert K. Nowicki and published by Springer. This book was released on 2018-12-17 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates an original concept for implementing the rough set theory in the construction of decision-making systems. It addresses three types of decisions, including those in which the information or input data is insufficient. Though decision-making and classification in cases with missing or inaccurate data is a common task, classical decision-making systems are not naturally adapted to it. One solution is to apply the rough set theory proposed by Prof. Pawlak. The proposed classifiers are applied and tested in two configurations: The first is an iterative mode in which a single classification system requests completion of the input data until an unequivocal decision (classification) is obtained. It allows us to start classification processes using very limited input data and supplementing it only as needed, which limits the cost of obtaining data. The second configuration is an ensemble mode in which several rough set-based classification systems achieve the unequivocal decision collectively, even though the systems cannot separately deliver such results.

Author : Lech Polkowski
Publisher : Physica
ISBN 13 : 3790818402
Total Pages : 679 pages
Book Rating : 4.06/5 ( download)

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Download or read book Rough Set Methods and Applications written by Lech Polkowski and published by Physica. This book was released on 2012-10-07 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Muhammad Summair Raza
Publisher : Springer Nature
ISBN 13 : 9813291664
Total Pages : 236 pages
Book Rating : 4.69/5 ( download)

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Download or read book Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications written by Muhammad Summair Raza and published by Springer Nature. This book was released on 2019-08-23 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms. The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.

Author : Guoyin Wang
Publisher : Springer
ISBN 13 : 354039205X
Total Pages : 758 pages
Book Rating : 4.57/5 ( download)

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Download or read book Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing written by Guoyin Wang and published by Springer. This book was released on 2003-08-03 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers selected for presentation at the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2003) held at Chongqing University of Posts and Telecommunications, Chongqing, P.R. China, May 26–29, 2003. There were 245 submissions for RSFDGrC 2003 excluding for 2 invited keynote papers and 11 invited plenary papers. Apart from the 13 invited papers, 114 papers were accepted for RSFDGrC 2003 and were included in this volume. The acceptance rate was only 46.5%. These papers were divided into 39 regular oral presentation papers (each allotted 8 pages), 47 short oral presentation papers (each allotted 4 pages) and 28 poster presentation papers (each allotted 4 pages) on the basis of reviewer evaluations. Each paper was reviewed by three referees. The conference is a continuation and expansion of the International Workshops on Rough Set Theory and Applications. In particular, this was the ninth meeting in the series and the first international conference. The aim of RSFDGrC2003 was to bring together researchers from diverse fields of expertise in order to facilitate mutual understanding and cooperation and to help in cooperative work aimed at new hybrid paradigms. It is our great pleasure to dedicate this volume to Prof. Zdzislaw Pawlak, who first introduced the basic ideas and definitions of rough sets theory over 20 years ago.

Author : Ewa Orlowska
Publisher : Physica
ISBN 13 : 3790818887
Total Pages : 615 pages
Book Rating : 4.88/5 ( download)

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Download or read book Incomplete Information: Rough Set Analysis written by Ewa Orlowska and published by Physica. This book was released on 2013-03-14 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1982, Professor Pawlak published his seminal paper on what he called "rough sets" - a work which opened a new direction in the development of theories of incomplete information. Today, a decade and a half later, the theory of rough sets has evolved into a far-reaching methodology for dealing with a wide variety of issues centering on incompleteness and imprecision of information - issues which playa key role in the conception and design of intelligent information systems. "Incomplete Information: Rough Set Analysis" - or RSA for short - presents an up-to-date and highly authoritative account of the current status of the basic theory, its many extensions and wide-ranging applications. Edited by Professor Ewa Orlowska, one of the leading contributors to the theory of rough sets, RSA is a collection of nineteen well-integrated chapters authored by experts in rough set theory and related fields. A common thread that runs through these chapters ties the concept of incompleteness of information to those of indiscernibility and similarity.

Author : Hiroshi Sakai
Publisher : Springer Science & Business Media
ISBN 13 : 3642215629
Total Pages : 241 pages
Book Rating : 4.29/5 ( download)

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Download or read book Transactions on Rough Sets XIV written by Hiroshi Sakai and published by Springer Science & Business Media. This book was released on 2011-07-05 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XIV contains 11 revised extended papers from the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2009, held in Delhi, India. The topics include various rough set generalizations in combination with formal concept analysis, lattice theory, fuzzy sets and belief functions, rough and fuzzy clustering techniques, as well as applications to gene selection, web page recommendation systems, facial recognition, and temporal pattern detection. in addition, this volume contains a regular article on rough multiset and its multiset topology.

Author : Julián Luengo
Publisher : Springer Nature
ISBN 13 : 3030391051
Total Pages : 193 pages
Book Rating : 4.58/5 ( download)

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Download or read book Big Data Preprocessing written by Julián Luengo and published by Springer Nature. This book was released on 2020-03-16 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensible overview of Big Data Preprocessing, which includes a formal description of each problem. It also focuses on the most relevant proposed solutions. This book illustrates actual implementations of algorithms that helps the reader deal with these problems. This book stresses the gap that exists between big, raw data and the requirements of quality data that businesses are demanding. This is called Smart Data, and to achieve Smart Data the preprocessing is a key step, where the imperfections, integration tasks and other processes are carried out to eliminate superfluous information. The authors present the concept of Smart Data through data preprocessing in Big Data scenarios and connect it with the emerging paradigms of IoT and edge computing, where the end points generate Smart Data without completely relying on the cloud. Finally, this book provides some novel areas of study that are gathering a deeper attention on the Big Data preprocessing. Specifically, it considers the relation with Deep Learning (as of a technique that also relies in large volumes of data), the difficulty of finding the appropriate selection and concatenation of preprocessing techniques applied and some other open problems. Practitioners and data scientists who work in this field, and want to introduce themselves to preprocessing in large data volume scenarios will want to purchase this book. Researchers that work in this field, who want to know which algorithms are currently implemented to help their investigations, may also be interested in this book.

Author : Bozena Kostek
Publisher : Springer Science & Business Media
ISBN 13 : 9783540257295
Total Pages : 440 pages
Book Rating : 4.92/5 ( download)

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Download or read book Perception-Based Data Processing in Acoustics written by Bozena Kostek and published by Springer Science & Business Media. This book was released on 2005-08-19 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides novel insights into cognitive mechanisms underlying the processing of sound and music in different environments. A solid understanding of these mechanisms is vital for numerous technological applications such as for example information retrieval from distributed musical databases or building expert systems. In order to investigate the cognitive mechanisms of music perception fundamentals of hearing psychophysiology and principles of music perception are presented. In addition, some computational intelligence methods are reviewed, such as rough sets, fuzzy logic, artificial neural networks, decision trees and genetic algorithms. The applications of hybrid decision systems to problem solving in music and acoustics are exemplified and discussed on the basis of obtained experimental results.

Author : Shi-Yu Huang
Publisher : Springer
ISBN 13 : 9789048141944
Total Pages : 0 pages
Book Rating : 4.4X/5 ( download)

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Download or read book Intelligent Decision Support written by Shi-Yu Huang and published by Springer. This book was released on 2010-12-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent decision support is based on human knowledge related to a specific part of a real or abstract world. When the knowledge is gained by experience, it is induced from empirical data. The data structure, called an information system, is a record of objects described by a set of attributes. Knowledge is understood here as an ability to classify objects. Objects being in the same class are indiscernible by means of attributes and form elementary building blocks (granules, atoms). In particular, the granularity of knowledge causes that some notions cannot be expressed precisely within available knowledge and can be defined only vaguely. In the rough sets theory created by Z. Pawlak each imprecise concept is replaced by a pair of precise concepts called its lower and upper approximation. These approximations are fundamental tools and reasoning about knowledge. The rough sets philosophy turned out to be a very effective, new tool with many successful real-life applications to its credit. It is worthwhile stressing that no auxiliary assumptions are needed about data, like probability or membership function values, which is its great advantage. The present book reveals a wide spectrum of applications of the rough set concept, giving the reader the flavor of, and insight into, the methodology of the newly developed disciplines. Although the book emphasizes applications, comparison with other related methods and further developments receive due attention.

Author : Aboul Ella Hassanien
Publisher : Springer
ISBN 13 : 331911056X
Total Pages : 502 pages
Book Rating : 4.61/5 ( download)

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Download or read book Big Data in Complex Systems written by Aboul Ella Hassanien and published by Springer. This book was released on 2015-01-02 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.