Synergies Of Soft Computing And Statistics For Intelligent Data Analysis

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Synergies of Soft Computing and Statistics for Intelligent Data Analysis

Rudolf Kruse,Michael R. Berthold,Christian Moewes,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz
Synergies of Soft Computing and Statistics for Intelligent Data Analysis Book PDF

Author : Rudolf Kruse,Michael R. Berthold,Christian Moewes,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz
Publisher : Springer
Page : 584 pages
File Size : 44,7 Mb
Release : 2012-09-14
Category : Computers
ISBN : 3642330436

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Synergies of Soft Computing and Statistics for Intelligent Data Analysis by Rudolf Kruse,Michael R. Berthold,Christian Moewes,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz Pdf

In recent years there has been a growing interest to extend classical methods for data analysis. The aim is to allow a more flexible modeling of phenomena such as uncertainty, imprecision or ignorance. Such extensions of classical probability theory and statistics are useful in many real-life situations, since uncertainties in data are not only present in the form of randomness --- various types of incomplete or subjective information have to be handled. About twelve years ago the idea of strengthening the dialogue between the various research communities in the field of data analysis was born and resulted in the International Conference Series on Soft Methods in Probability and Statistics (SMPS). This book gathers contributions presented at the SMPS'2012 held in Konstanz, Germany. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems.

Synergies of Soft Computing and Statistics for Intelligent Data Analysis

Rudolf Kruse,Michael R. Berthold,Christian Moewes,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz
Synergies of Soft Computing and Statistics for Intelligent Data Analysis Book PDF

Author : Rudolf Kruse,Michael R. Berthold,Christian Moewes,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz
Publisher : Springer Science & Business Media
Page : 555 pages
File Size : 42,5 Mb
Release : 2012-09-13
Category : Technology & Engineering
ISBN : 9783642330421

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Synergies of Soft Computing and Statistics for Intelligent Data Analysis by Rudolf Kruse,Michael R. Berthold,Christian Moewes,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz Pdf

In recent years there has been a growing interest to extend classical methods for data analysis. The aim is to allow a more flexible modeling of phenomena such as uncertainty, imprecision or ignorance. Such extensions of classical probability theory and statistics are useful in many real-life situations, since uncertainties in data are not only present in the form of randomness --- various types of incomplete or subjective information have to be handled. About twelve years ago the idea of strengthening the dialogue between the various research communities in the field of data analysis was born and resulted in the International Conference Series on Soft Methods in Probability and Statistics (SMPS). This book gathers contributions presented at the SMPS'2012 held in Konstanz, Germany. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems.

Strengthening Links Between Data Analysis and Soft Computing

Przemyslaw Grzegorzewski,Marek Gagolewski,Olgierd Hryniewicz,María Ángeles Gil
Strengthening Links Between Data Analysis and Soft Computing Book PDF

Author : Przemyslaw Grzegorzewski,Marek Gagolewski,Olgierd Hryniewicz,María Ángeles Gil
Publisher : Springer
Page : 294 pages
File Size : 55,8 Mb
Release : 2014-09-10
Category : Technology & Engineering
ISBN : 9783319107653

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Strengthening Links Between Data Analysis and Soft Computing by Przemyslaw Grzegorzewski,Marek Gagolewski,Olgierd Hryniewicz,María Ángeles Gil Pdf

This book gathers contributions presented at the 7th International Conference on Soft Methods in Probability and Statistics SMPS 2014, held in Warsaw (Poland) on September 22-24, 2014. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems.

Guide to Intelligent Data Analysis

Michael R. Berthold,Christian Borgelt,Frank Höppner,Frank Klawonn
Guide to Intelligent Data Analysis Book PDF

Author : Michael R. Berthold,Christian Borgelt,Frank Höppner,Frank Klawonn
Publisher : Springer Science & Business Media
Page : 399 pages
File Size : 43,9 Mb
Release : 2010-06-23
Category : Computers
ISBN : 9781848822603

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Guide to Intelligent Data Analysis by Michael R. Berthold,Christian Borgelt,Frank Höppner,Frank Klawonn Pdf

Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle – solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of “drowning in information, but starving for knowledge” the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examples to support pedagogical exposition. This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one’s exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.

Advances in Intelligent Data Analysis. Reasoning about Data

Xiaohui Liu,Michael R. Berthold
Advances in Intelligent Data Analysis Reasoning about Data Book PDF

Author : Xiaohui Liu,Michael R. Berthold
Publisher : Springer Science & Business Media
Page : 644 pages
File Size : 51,9 Mb
Release : 1997-07-23
Category : Business & Economics
ISBN : 3540633464

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Advances in Intelligent Data Analysis. Reasoning about Data by Xiaohui Liu,Michael R. Berthold Pdf

This book constitutes the refereed proceedings of the Second International Symposium on Intelligent Data Analysis, IDA-97, held in London, UK, in August 1997. The volume presents 50 revised full papers selected from a total of 107 submissions. Also included is a keynote, Intelligent Data Analysis: Issues and Opportunities, by David J. Hand. The papers are organized in sections on exploratory data analysis, preprocessing and tools; classification and feature selection; medical applications; soft computing; knowledge discovery and data mining; estimation and clustering; data quality; qualitative models.

Recent Developments and New Directions in Soft Computing

Lotfi A. Zadeh,Ali M. Abbasov,Ronald R. Yager,Shahnaz N. Shahbazova,Marek Z. Reformat
Recent Developments and New Directions in Soft Computing Book PDF

Author : Lotfi A. Zadeh,Ali M. Abbasov,Ronald R. Yager,Shahnaz N. Shahbazova,Marek Z. Reformat
Publisher : Springer
Page : 450 pages
File Size : 53,7 Mb
Release : 2014-06-17
Category : Technology & Engineering
ISBN : 9783319063232

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Recent Developments and New Directions in Soft Computing by Lotfi A. Zadeh,Ali M. Abbasov,Ronald R. Yager,Shahnaz N. Shahbazova,Marek Z. Reformat Pdf

The book reports on the latest advances and challenges of soft computing. It gathers original scientific contributions written by top scientists in the field and covering theories, methods and applications in a number of research areas related to soft-computing, such as decision-making, probabilistic reasoning, image processing, control, neural networks and data analysis.

Intelligent Data Analysis

Michael R. Berthold,David J Hand
Intelligent Data Analysis Book PDF

Author : Michael R. Berthold,David J Hand
Publisher : Springer
Page : 515 pages
File Size : 50,6 Mb
Release : 2007-06-07
Category : Computers
ISBN : 9783540486251

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Intelligent Data Analysis by Michael R. Berthold,David J Hand Pdf

This second and revised edition contains a detailed introduction to the key classes of intelligent data analysis methods. The twelve coherently written chapters by leading experts provide complete coverage of the core issues. The first half of the book is devoted to the discussion of classical statistical issues. The following chapters concentrate on machine learning and artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a chapter on visualization and an advanced overview of IDA processes.

Computational Intelligence

Rudolf Kruse,Christian Borgelt,Christian Braune,Sanaz Mostaghim,Matthias Steinbrecher
Computational Intelligence Book PDF

Author : Rudolf Kruse,Christian Borgelt,Christian Braune,Sanaz Mostaghim,Matthias Steinbrecher
Publisher : Springer
Page : 564 pages
File Size : 45,9 Mb
Release : 2016-09-16
Category : Computers
ISBN : 9781447172963

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Computational Intelligence by Rudolf Kruse,Christian Borgelt,Christian Braune,Sanaz Mostaghim,Matthias Steinbrecher Pdf

This textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced second edition has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs. Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.

Combining Soft Computing and Statistical Methods in Data Analysis

Christian Borgelt,Gil González Rodríguez,Wolfgang Trutschnig,María Asunción Lubiano,María Angeles Gil,Przemyslaw Grzegorzewski,Olgierd Hryniewicz
Combining Soft Computing and Statistical Methods in Data Analysis Book PDF

Author : Christian Borgelt,Gil González Rodríguez,Wolfgang Trutschnig,María Asunción Lubiano,María Angeles Gil,Przemyslaw Grzegorzewski,Olgierd Hryniewicz
Publisher : Springer Science & Business Media
Page : 640 pages
File Size : 47,9 Mb
Release : 2010-10-12
Category : Technology & Engineering
ISBN : 9783642147463

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Combining Soft Computing and Statistical Methods in Data Analysis by Christian Borgelt,Gil González Rodríguez,Wolfgang Trutschnig,María Asunción Lubiano,María Angeles Gil,Przemyslaw Grzegorzewski,Olgierd Hryniewicz Pdf

Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.

Uncertainty Modelling in Data Science

Sébastien Destercke,Thierry Denoeux,María Ángeles Gil,Przemyslaw Grzegorzewski,Olgierd Hryniewicz
Uncertainty Modelling in Data Science Book PDF

Author : Sébastien Destercke,Thierry Denoeux,María Ángeles Gil,Przemyslaw Grzegorzewski,Olgierd Hryniewicz
Publisher : Springer
Page : 234 pages
File Size : 48,6 Mb
Release : 2018-07-24
Category : Technology & Engineering
ISBN : 9783319975474

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Uncertainty Modelling in Data Science by Sébastien Destercke,Thierry Denoeux,María Ángeles Gil,Przemyslaw Grzegorzewski,Olgierd Hryniewicz Pdf

This book features 29 peer-reviewed papers presented at the 9th International Conference on Soft Methods in Probability and Statistics (SMPS 2018), which was held in conjunction with the 5th International Conference on Belief Functions (BELIEF 2018) in Compiègne, France on September 17–21, 2018. It includes foundational, methodological and applied contributions on topics as varied as imprecise data handling, linguistic summaries, model coherence, imprecise Markov chains, and robust optimisation. These proceedings were produced using EasyChair. Over recent decades, interest in extensions and alternatives to probability and statistics has increased significantly in diverse areas, including decision-making, data mining and machine learning, and optimisation. This interest stems from the need to enrich existing models, in order to include different facets of uncertainty, like ignorance, vagueness, randomness, conflict or imprecision. Frameworks such as rough sets, fuzzy sets, fuzzy random variables, random sets, belief functions, possibility theory, imprecise probabilities, lower previsions, and desirable gambles all share this goal, but have emerged from different needs. The advances, results and tools presented in this book are important in the ubiquitous and fast-growing fields of data science, machine learning and artificial intelligence. Indeed, an important aspect of some of the learned predictive models is the trust placed in them. Modelling the uncertainty associated with the data and the models carefully and with principled methods is one of the means of increasing this trust, as the model will then be able to distinguish between reliable and less reliable predictions. In addition, extensions such as fuzzy sets can be explicitly designed to provide interpretable predictive models, facilitating user interaction and increasing trust.

Fuzzy Statistical Decision-Making

Cengiz Kahraman,Özgür Kabak
Fuzzy Statistical Decision Making Book PDF

Author : Cengiz Kahraman,Özgür Kabak
Publisher : Springer
Page : 356 pages
File Size : 41,5 Mb
Release : 2016-07-15
Category : Technology & Engineering
ISBN : 9783319390147

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Fuzzy Statistical Decision-Making by Cengiz Kahraman,Özgür Kabak Pdf

This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.

Logic and Uncertainty in the Human Mind

Shira Elqayam,Igor Douven,Jonathan St B. T. Evans,Nicole Cruz
Logic and Uncertainty in the Human Mind Book PDF

Author : Shira Elqayam,Igor Douven,Jonathan St B. T. Evans,Nicole Cruz
Publisher : Routledge
Page : 264 pages
File Size : 45,7 Mb
Release : 2020-06-10
Category : Psychology
ISBN : 9781351620413

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Logic and Uncertainty in the Human Mind by Shira Elqayam,Igor Douven,Jonathan St B. T. Evans,Nicole Cruz Pdf

David E. Over is a leading cognitive scientist and, with his firm grounding in philosophical logic, he also exerts a powerful influence on the psychology of reasoning. He is responsible for not only a large body of empirical work and accompanying theory, but for advancing a major shift in thinking about reasoning, commonly known as the ‘new paradigm’ in the psychology of human reasoning. Over’s signature mix of philosophical logic and experimental psychology has inspired generations of researchers, psychologists, and philosophers alike over more than a quarter of a century. The chapters in this volume, written by a leading group of contributors including a number who helped shape the psychology of reasoning as we know it today, each take their starting point from the key themes of Over’s ground-breaking work. The essays in this collection explore a wide range of central topics—such as rationality, bias, dual processes, and dual systems—as well as contemporary psychological and philosophical theories of conditionals. It concludes with an engaging new chapter, authored by David E. Over himself, which details and analyses the new paradigm psychology of reasoning. This book is therefore important reading for scholars, researchers, and advanced students in psychology, philosophy, and the cognitive sciences, including those who are not familiar with Over’s thought already.

Soft Computing Applications for Group Decision-making and Consensus Modeling

Mikael Collan,Janusz Kacprzyk
Soft Computing Applications for Group Decision making and Consensus Modeling Book PDF

Author : Mikael Collan,Janusz Kacprzyk
Publisher : Springer
Page : 488 pages
File Size : 43,7 Mb
Release : 2017-06-30
Category : Technology & Engineering
ISBN : 9783319602073

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Soft Computing Applications for Group Decision-making and Consensus Modeling by Mikael Collan,Janusz Kacprzyk Pdf

This book offers a concise introduction and comprehensive overview of the state of the art in the field of decision-making and consensus modeling, with a special emphasis on fuzzy methods. It consists of a collection of authoritative contributions reporting on the decision-making process from different perspectives: from psychology to social and political sciences, from decision sciences to data mining, and from computational sciences in general, to artificial and computational intelligence and systems. Written as a homage to Mario Fedrizzi for his scholarly achievements, creative ideas and long lasting services to different scientific communities, it introduces key theoretical concepts, describes new models and methods, and discusses a range of promising real-world applications in the field of decision-making science. It is a timely reference guide and a source of inspiration for advanced students and researchers

Soft Methods for Data Science

Maria Brigida Ferraro,Paolo Giordani,Barbara Vantaggi,Marek Gagolewski,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz
Soft Methods for Data Science Book PDF

Author : Maria Brigida Ferraro,Paolo Giordani,Barbara Vantaggi,Marek Gagolewski,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz
Publisher : Springer
Page : 535 pages
File Size : 44,6 Mb
Release : 2016-08-30
Category : Technology & Engineering
ISBN : 9783319429724

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Soft Methods for Data Science by Maria Brigida Ferraro,Paolo Giordani,Barbara Vantaggi,Marek Gagolewski,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz Pdf

This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.

Copulae in Mathematical and Quantitative Finance

Piotr Jaworski,Fabrizio Durante,Wolfgang Karl Härdle
Copulae in Mathematical and Quantitative Finance Book PDF

Author : Piotr Jaworski,Fabrizio Durante,Wolfgang Karl Härdle
Publisher : Springer Science & Business Media
Page : 299 pages
File Size : 47,6 Mb
Release : 2013-06-18
Category : Business & Economics
ISBN : 9783642354076

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Copulae in Mathematical and Quantitative Finance by Piotr Jaworski,Fabrizio Durante,Wolfgang Karl Härdle Pdf

Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models. Since their introduction in the early 1950s, copulas have gained considerable popularity in several fields of applied mathematics, especially finance and insurance. Today, copulas represent a well-recognized tool for market and credit models, aggregation of risks, and portfolio selection. Historically, the Gaussian copula model has been one of the most common models in credit risk. However, the recent financial crisis has underlined its limitations and drawbacks. In fact, despite their simplicity, Gaussian copula models severely underestimate the risk of the occurrence of joint extreme events. Recent theoretical investigations have put new tools for detecting and estimating dependence and risk (like tail dependence, time-varying models, etc) in the spotlight. All such investigations need to be further developed and promoted, a goal this book pursues. The book includes surveys that provide an up-to-date account of essential aspects of copula models in quantitative finance, as well as the extended versions of talks selected from papers presented at the workshop in Cracow.