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Topics In Rough Set Theory
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Download or read book Rough Sets written by Lech Polkowski and published by Springer Science & Business Media. This book was released on 2013-06-05 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to mathematical structures essential for Rough Set Theory. The book enables the reader to systematically study all topics of rough set theory. After a detailed introduction in Part 1 along with an extensive bibliography of current research papers. Part 2 presents a self-contained study that brings together all the relevant information from respective areas of mathematics and logics. Part 3 provides an overall picture of theoretical developments in rough set theory, covering logical, algebraic, and topological methods. Topics covered include: algebraic theory of approximation spaces, logical and set-theoretical approaches to indiscernibility and functional dependence, topological spaces of rough sets. The final part gives a unique view on mutual relations between fuzzy and rough set theories (rough fuzzy and fuzzy rough sets). Over 300 excercises allow the reader to master the topics considered. The book can be used as a textbook and as a reference work.
Book Synopsis Rough Set Theory: A True Landmark in Data Analysis by : Ajith Abraham
Download or read book Rough Set Theory: A True Landmark in Data Analysis written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2009-02-26 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part 1 of this book deals with theoretical contributions of rough set theory, and parts 2 and 3 focus on several real world data mining applications. The book thoroughly explores recent results in rough set research.
Download or read book Rough Sets written by Z. Pawlak and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Rough Sets and Data Mining by : T.Y. Lin
Download or read book Rough Sets and Data Mining written by T.Y. Lin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Transactions on Rough Sets II by : James F. Peters
Download or read book Transactions on Rough Sets II written by James F. Peters and published by Springer. This book was released on 2004-11-29 with total page 363 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, starting 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. This second volume of the Transactions on Rough Sets presents 17 thoroughly reviewed revised papers devoted to rough set theory, fuzzy set theory; these papers highlight important aspects of these theories, their interrelation and application in various fields.
Book Synopsis Incomplete Information: Rough Set Analysis by : Ewa Orlowska
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.
Book Synopsis Topics in Rough Set Theory by : Seiki Akama
Download or read book Topics in Rough Set Theory written by Seiki Akama and published by Springer Nature. This book was released on 2019-09-10 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses current topics in rough set theory. Since Pawlak’s rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.
Book Synopsis Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications by : Muhammad Summair Raza
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.
Book Synopsis Rough Set Methods and Applications by : Lech Polkowski
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.
Book Synopsis Big Data Preprocessing by : Julián Luengo
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.
Book Synopsis A Geometry of Approximation by : Piero Pagliani
Download or read book A Geometry of Approximation written by Piero Pagliani and published by Springer Science & Business Media. This book was released on 2008-10-09 with total page 771 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'A Geometry of Approximation' addresses Rough Set Theory, a field of interdisciplinary research first proposed by Zdzislaw Pawlak in 1982, and focuses mainly on its logic-algebraic interpretation. The theory is embedded in a broader perspective that includes logical and mathematical methodologies pertaining to the theory, as well as related epistemological issues. Any mathematical technique that is introduced in the book is preceded by logical and epistemological explanations. Intuitive justifications are also provided, insofar as possible, so that the general perspective is not lost. Such an approach endows the present treatise with a unique character. Due to this uniqueness in the treatment of the subject, the book will be useful to researchers, graduate and pre-graduate students from various disciplines, such as computer science, mathematics and philosophy. It features an impressive number of examples supported by about 40 tables and 230 figures. The comprehensive index of concepts turns the book into a sort of encyclopaedia for researchers from a number of fields. 'A Geometry of Approximation' links many areas of academic pursuit without losing track of its focal point, Rough Sets.
Book Synopsis Rough Set Theory: A True Landmark in Data Analysis by : Ajith Abraham
Download or read book Rough Set Theory: A True Landmark in Data Analysis written by Ajith Abraham and published by Springer. This book was released on 2008-12-23 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Along the years, rough set theory has earned a well-deserved reputation as a sound methodology for dealing with imperfect knowledge in a simple though mathematically sound way. This edited volume aims at continue stressing the benefits of applying rough sets in many real-life situations while still keeping an eye on topological aspects of the theory as well as strengthening its linkage with other soft computing paradigms. The volume comprises 11 chapters and is organized into three parts. Part 1 deals with theoretical contributions while Parts 2 and 3 focus on several real world data mining applications. Chapters authored by pioneers were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed. Academics, scientists as well as engineers working in the rough set, computational intelligence, soft computing and data mining research area will find the comprehensive coverage of this book invaluable.
Book Synopsis Data Mining and Knowledge Discovery in Real Life Applications by : Julio Ponce
Download or read book Data Mining and Knowledge Discovery in Real Life Applications written by Julio Ponce and published by BoD – Books on Demand. This book was released on 2009-01-01 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.
Book Synopsis Practical Applications of Data Mining by : Sang Suh
Download or read book Practical Applications of Data Mining written by Sang Suh and published by Jones & Bartlett Publishers. This book was released on 2012 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.
Book Synopsis Transactions on Rough Sets I by : James F. Peters
Download or read book Transactions on Rough Sets I written by James F. Peters and published by Springer Science & Business Media. This book was released on 2004-07-05 with total page 414 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, starting 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. This first volume of the Transactions on Rough Sets opens with an introductory article by Zdzislaw Pawlak, the originator of rough sets. Nine papers deal with rough set theory and eight are devoted to applications in various domains.
Book Synopsis Knowledge Representation Techniques by : Patrick Doherty
Download or read book Knowledge Representation Techniques written by Patrick Doherty and published by Springer. This book was released on 2007-05-31 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a cohesive, self-contained collection of theoretical and applied research results that have been achieved in this project which pertain to nonmonotonic and approximate easoning systems developed for an experimental unmanned aerial vehicle system used in the project. This book should be of interest to the theoretician and applied researcher alike and to autonomous system developers and software agent and intelligent system developers.
Book Synopsis Transactions on Rough Sets XII by : James F. Peters
Download or read book Transactions on Rough Sets XII written by James F. Peters and published by Springer Science & Business Media. This book was released on 2010-07-15 with total page 348 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. This volume contains 8 revised selected papers from 11 submissions to the Rough Set and Knowledge Technology Conference (RSKT 2008), together with 5 papers introducing advances in rough set theory and its applications. The topics covered are: perceptually near Pawlak partitions, hypertext classification, topological space versus rough set theory in terms of lattice theory, feature extraction in interval-valued information systems, jumping emerging patterns (JEP), and rough set theory.
