Download or read book Data Analysis Learning Symbolic and Numeric Knowledge written by E. Diday and published by Nova Biomedical Books. This book was released on 1989 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis, Learning Symbolic & Numeric Knowledge Proceedings Of The Conference On Data Analysis, Learning Symbolic & Numeric Knowledge

Download or read book Data Analysis Learning Symbolic and Numeric Knowledge written by E. Diday and published by . This book was released on 1989 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Symbolic numeric Data Analysis and Learning written by E. Diday and published by . This book was released on 1991 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings of an international conference held in Paris, France, September 1991, present the latest achievements in theory, methodology, and software tools which should allow a better understanding of the data which have been collected. Sessions are devoted to metrics, robust methods, applicati

Download or read book Symbolic Data Analysis written by Lynne Billard and published by John Wiley & Sons. This book was released on 2012-05-14 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of computers, very large datasets have become routine. Standard statistical methods don’t have the power or flexibility to analyse these efficiently, and extract the required knowledge. An alternative approach is to summarize a large dataset in such a way that the resulting summary dataset is of a manageable size and yet retains as much of the knowledge in the original dataset as possible. One consequence of this is that the data may no longer be formatted as single values, but be represented by lists, intervals, distributions, etc. The summarized data have their own internal structure, which must be taken into account in any analysis. This text presents a unified account of symbolic data, how they arise, and how they are structured. The reader is introduced to symbolic analytic methods described in the consistent statistical framework required to carry out such a summary and subsequent analysis. Presents a detailed overview of the methods and applications of symbolic data analysis. Includes numerous real examples, taken from a variety of application areas, ranging from health and social sciences, to economics and computing. Features exercises at the end of each chapter, enabling the reader to develop their understanding of the theory. Provides a supplementary website featuring links to download the SODAS software developed exclusively for symbolic data analysis, data sets, and further material. Primarily aimed at statisticians and data analysts, Symbolic Data Analysis is also ideal for scientists working on problems involving large volumes of data from a range of disciplines, including computer science, health and the social sciences. There is also much of use to graduate students of statistical data analysis courses.

Download or read book New Approaches in Classification and Data Analysis written by Edwin Diday and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this book is the analysis and processing of structural or quantitative data with emphasis on classification methods, new algorithms as well as applications in various fields related to data analysis and classification. The book presents the state of the art in world-wide research and application of methods from the fields indicated above and consists of survey papers as well as research papers.

Download or read book Analysis of Symbolic Data written by Hans-Hermann Bock and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphical data analysis to the case of complex data. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.

Download or read book Classification Data Analysis and Knowledge Organization written by Hans-Hermann Bock and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: In science, industry, public administration and documentation centers large amounts of data and information are collected which must be analyzed, ordered, visualized, classified and stored efficiently in order to be useful for practical applications. This volume contains 50 selected theoretical and applied papers presenting a wealth of new and innovative ideas, methods, models and systems which can be used for this purpose. It combines papers and strategies from two main streams of research in an interdisciplinary, dynamic and exciting way: On the one hand, mathematical and statistical methods are described which allow a quantitative analysis of data, provide strategies for classifying objects or making exploratory searches for interesting structures, and give ways to make comprehensive graphical displays of large arrays of data. On the other hand, papers related to information sciences, informatics and data bank systems provide powerful tools for representing, modelling, storing and retrieving facts, data and knowledge characterized by qualitative descriptors, semantic relations, or linguistic concepts. The integration of both fields and a special part on applied problems from biology, medicine, archeology, industry and administration assure that this volume will be informative and useful for theory and practice.

Download or read book Data Analysis Machine Learning and Knowledge Discovery written by Myra Spiliopoulou and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012. ​

Download or read book Cluster Analysis for Data Mining and System Identification written by János Abonyi and published by Springer Science & Business Media. This book was released on 2007-08-10 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.

Download or read book Applied Stochastic Models And Data Analysis Proceedings Of The Fifth International Symposium On Asmda written by Valderrama M J and published by #N/A. This book was released on 1991-03-29 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: As with previous symposiums, the main objective of the Sixth International Symposium is to publish papers (of both technical and practical nature) to present new findings uncovered by theoretical results which may have the potential to contribute solutions to real-life problems. With this objective in mind, this collection of papers aims to serve as an interface between stochastic modeling and data analysis as well as their applications to the problems we face in the various fields. The papers first focused on the theory, application and interaction between stochastic models and data analysis. The results and their applications to the problems we face in the fields of economics, finance and insurance, management, marketing, health sciences, production and engineering are then explored.

Download or read book Axiomatic Fuzzy Set Theory and Its Applications written by Xiaodong Liu and published by Springer Science & Business Media. This book was released on 2009-04-07 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is well known that “fuzziness”—informationgranulesand fuzzy sets as one of its formal manifestations— is one of important characteristics of human cognitionandcomprehensionofreality. Fuzzy phenomena existinnature and are encountered quite vividly within human society. The notion of a fuzzy set has been introduced by L. A. , Zadeh in 1965 in order to formalize human concepts, in connection with the representation of human natural language and computing with words. Fuzzy sets and fuzzy logic are used for mod- ing imprecise modes of reasoning that play a pivotal role in the remarkable human abilities to make rational decisions in an environment a?ected by - certainty and imprecision. A growing number of applications of fuzzy sets originated from the “empirical-semantic” approach. From this perspective, we were focused on some practical interpretations of fuzzy sets rather than being oriented towards investigations of the underlying mathematical str- tures of fuzzy sets themselves. For instance, in the context of control theory where fuzzy sets have played an interesting and practically relevant function, the practical facet of fuzzy sets has been stressed quite signi?cantly. However, fuzzy sets can be sought as an abstract concept with all formal underpinnings stemming from this more formal perspective. In the context of applications, it is worth underlying that membership functions do not convey the same meaning at the operational level when being cast in various contexts.

Download or read book Conceptual Structures Fulfilling Peirce s Dream written by Dickson Lukose and published by Springer Science & Business Media. This book was released on 1997-07-16 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Fifth International Conference on Conceptual Structures, ICCS '97, held in Seattle, Washington, USA, in August 1997. The 39 full papers presented were carefully selected and revised for inclusion in the volume. Also included are 9 abstracts of conceptual graphs tools. The papers are organized in sections on knowledge representation, knowledge modeling, formal concept analysis, formal reasoning, applications of conceptual graphs, and conceptual graphs tools. This book competently documents the progress achieved in the area since the predecessor conference ICCS '96, the proceedings of which have been published as LNAI 1115.

Download or read book Data Mining and Data Visualization written by and published by Elsevier. This book was released on 2005-05-02 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. Distinguished contributors who are international experts in aspects of data mining Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions Thorough discussion of data visualization issues blending statistical, human factors, and computational insights

Download or read book Advances in Data Mining written by Petra Perner and published by Springer. This book was released on 2006-07-13 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th Industrial Conference on Data Mining, ICDM 2006, held in Leipzig, Germany in July 2006. Presents 45 carefully reviewed and revised full papers organized in topical sections on data mining in medicine, Web mining and logfile analysis, theoretical aspects of data mining, data mining in marketing, mining signals and images, and aspects of data mining, and applications such as intrusion detection, and more.

Download or read book Rough Sets Fuzzy Sets and Knowledge Discovery written by Wojciech P. Ziarko and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is two-fold. Firstly, it is aimed at bringing to gether key research articles concerned with methodologies for knowledge discovery in databases and their applications. Secondly, it also contains articles discussing fundamentals of rough sets and their relationship to fuzzy sets, machine learning, management of uncertainty and systems of logic for formal reasoning about knowledge. Applications of rough sets in different areas such as medicine, logic design, image processing and expert systems are also represented. The articles included in the book are based on selected papers presented at the International Workshop on Rough Sets and Knowledge Discovery held in Banff, Canada in 1993. The primary methodological approach emphasized in the book is the mathematical theory of rough sets, a relatively new branch of mathematics concerned with the modeling and analysis of classification problems with imprecise, uncertain, or incomplete information. The methods of the theory of rough sets have applications in many sub-areas of artificial intelligence including knowledge discovery, machine learning, formal reasoning in the presence of uncertainty, knowledge acquisition, and others. This spectrum of applications is reflected in this book where articles, although centered around knowledge discovery problems, touch a number of related issues. The book is intended to provide an important reference material for students, researchers, and developers working in the areas of knowledge discovery, machine learning, reasoning with uncertainty, adaptive expert systems, and pattern classification.

Download or read book Fuzzy Systems and Knowledge Discovery written by Lipo Wang and published by Springer. This book was released on 2005-08-25 with total page 1374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book and its sister volume, LNAI 3613 and 3614, constitute the proce- ings of the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005), jointly held with the First International Conference on Natural Computation (ICNC 2005, LNCS 3610, 3611, and 3612) from - gust 27–29, 2005 in Changsha, Hunan, China. FSKD 2005 successfully attracted 1249 submissions from 32 countries/regions (the joint ICNC-FSKD 2005 received 3136 submissions). After rigorous reviews, 333 high-quality papers, i. e. , 206 long papers and 127 short papers, were included in the FSKD 2005 proceedings, r- resenting an acceptance rate of 26. 7%. The ICNC-FSKD 2005 conference featured the most up-to-date research - sults in computational algorithms inspired from nature, including biological, e- logical, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a signi?cant impact on the advancement of these important technologies. Speci?c areas included computation with words, fuzzy computation, granular com- tation, neural computation, quantum computation, evolutionary computation, DNA computation, chemical computation, information processing in cells and tissues, molecular computation, arti?cial life, swarm intelligence, ants colony, arti?cial immune systems, etc. , with innovative applications to knowledge d- covery, ?nance, operations research, and more.

Download or read book Machine Learning written by Yves Kodratoff and published by Elsevier. This book was released on 2014-06-28 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning: An Artificial Intelligence Approach, Volume III presents a sample of machine learning research representative of the period between 1986 and 1989. The book is organized into six parts. Part One introduces some general issues in the field of machine learning. Part Two presents some new developments in the area of empirical learning methods, such as flexible learning concepts, the Protos learning apprentice system, and the WITT system, which implements a form of conceptual clustering. Part Three gives an account of various analytical learning methods and how analytic learning can be applied to various specific problems. Part Four describes efforts to integrate different learning strategies. These include the UNIMEM system, which empirically discovers similarities among examples; and the DISCIPLE multistrategy system, which is capable of learning with imperfect background knowledge. Part Five provides an overview of research in the area of subsymbolic learning methods. Part Six presents two types of formal approaches to machine learning. The first is an improvement over Mitchell's version space method; the second technique deals with the learning problem faced by a robot in an unfamiliar, deterministic, finite-state environment.