Towards Advanced Data Analysis by Combining Soft Computing and Statistics PDF Download
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Author: Christian Borgelt
Publisher: Springer
ISBN: 3642302785
Category : Technology & Engineering
Languages : en
Pages : 378
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Book Description
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.
Author: Christian Borgelt
Publisher: Springer
ISBN: 3642302785
Category : Technology & Engineering
Languages : en
Pages : 378
Get Book Here
Book Description
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.
Author: Luis A. García-Escudero
Publisher: Springer Nature
ISBN: 3031155092
Category : Computers
Languages : en
Pages : 421
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Book Description
Nowadays, data analysis is becoming an appealing topic due to the emergence of new data types, dimensions, and sources. This motivates the development of probabilistic/statistical approaches and tools to cope with these data. Different communities of experts, namely statisticians, mathematicians, computer scientists, engineers, econometricians, and psychologists are more and more interested in facing this challenge. As a consequence, there is a clear need to build bridges between all these communities for Data Science. This book contains more than fifty selected recent contributions aiming to establish the above referred bridges. These contributions address very different and relevant aspects such as imprecise probabilities, information theory, random sets and random fuzzy sets, belief functions, possibility theory, dependence modelling and copulas, clustering, depth concepts, dimensionality reduction of complex data and robustness.
Author: Rudolf Kruse
Publisher: Springer
ISBN: 1447172965
Category : Computers
Languages : en
Pages : 556
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Book Description
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.
Author: Sergey Kovalev
Publisher: Springer Nature
ISBN: 3030500977
Category : Technology & Engineering
Languages : en
Pages : 713
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Book Description
This book gathers papers presented in the main track of IITI 2019, the Fourth International Scientific Conference on Intelligent Information Technologies for Industry, held in Ostrava–Prague, Czech Republic on December 2–7, 2019. The conference was jointly organized by Rostov State Transport University (Russia) and VŠB – Technical University of Ostrava (Czech Republic) with the participation of the Russian Association for Artificial Intelligence (RAAI). IITI 2019 was devoted to practical models and industrial applications of intelligent information systems. Though chiefly intended to promote the implementation of advanced information technologies in various industries, topics such as the state of the art in intelligent systems and soft computing were also discussed.
Author: Rudolf Seising
Publisher: Springer
ISBN: 3319187503
Category : Technology & Engineering
Languages : en
Pages : 382
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Book Description
This book provides readers with a snapshot of the state-of-the art in fuzzy logic. Throughout the chapters, key theories developed in the last fifty years as well as important applications to practical problems are presented and discussed from different perspectives, as the authors hail from different disciplines and therefore use fuzzy logic for different purposes. The book aims at showing how fuzzy logic has evolved since the first theory formulation by Lotfi A. Zadeh in his seminal paper on Fuzzy Sets in 1965. Fuzzy theories and implementation grew at an impressive speed and achieved significant results, especially on the applicative side. The study of fuzzy logic and its practice spread all over the world, from Europe to Asia, America and Oceania. The editors believe that, thanks to the drive of young researchers, fuzzy logic will be able to face the challenging goals posed by computing with words. New frontiers of knowledge are waiting to be explored. In order to motivate young people to engage in the future development of fuzzy logic, fuzzy methodologies, fuzzy applications, etc., the editors invited a team of internationally respected experts to write the present collection of papers, which shows the present and future potentials of fuzzy logic from different disciplinary perspectives and personal standpoints.
Author: Francesco Masulli
Publisher: Springer
ISBN: 366248577X
Category : Computers
Languages : en
Pages : 157
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Book Description
This book constitutes the proceedings of the International Workshop on Clustering High-Dimensional Data, CHDD 2012, held in Naples, Italy, in May 2012. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the general subject and issues of high-dimensional data clustering; present examples of techniques used to find and investigate clusters in high dimensionality; and the most common approach to tackle dimensionality problems, namely, dimensionality reduction and its application in clustering.
Author: Ellen Gasparovic
Publisher: Springer
ISBN: 3030115666
Category : Mathematics
Languages : en
Pages : 302
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Book Description
This edited volume on data science features a variety of research ranging from theoretical to applied and computational topics. Aiming to establish the important connection between mathematics and data science, this book addresses cutting edge problems in predictive modeling, multi-scale representation and feature selection, statistical and topological learning, and related areas. Contributions study topics such as the hubness phenomenon in high-dimensional spaces, the use of a heuristic framework for testing the multi-manifold hypothesis for high-dimensional data, the investigation of interdisciplinary approaches to multi-dimensional obstructive sleep apnea patient data, and the inference of a dyadic measure and its simplicial geometry from binary feature data. Based on the first Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place in 2017 at the Institute for Compuational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, this volume features submissions from several of the working groups as well as contributions from the wider community. The volume is suitable for researchers in data science in industry and academia.
Author: Christian Beecks
Publisher: Springer
ISBN: 3319684744
Category : Computers
Languages : en
Pages : 337
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Book Description
This book constitutes the refereed proceedings of the 10th International Conference on Similarity Search and Applications, SISAP 2017, held in Munich, Germany, in October 2017. The 23 full papers presented were carefully reviewed and selected from 53 submissions. The papers deal with issues surrounding the theory, design, analysis, practice, and application of content-based and feature-based similarity search. They are organized in the following topical sections: approximate similarity search; improving similarity search methods and applications; distances for complex objects; outlier detection; indexing and applications; and applications and specific domains. The paper 'A New Perspective on the Tree Edit Distance' is published open access under a CC BY 4.0 license at link.springer.com.
Author: Xizhao Wang
Publisher: Springer
ISBN: 3662456524
Category : Computers
Languages : en
Pages : 460
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Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full papers presented were carefully reviewed and selected from 421 submissions. The papers are organized in topical sections on classification and semi-supervised learning; clustering and kernel; application to recognition; sampling and big data; application to detection; decision tree learning; learning and adaptation; similarity and decision making; learning with uncertainty; improved learning algorithms and applications.
Author: Michael R. Berthold
Publisher: Springer Science & Business Media
ISBN: 184882260X
Category : Computers
Languages : en
Pages : 399
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Book Description
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.
