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Applied Multidimensional Scaling

Applied Multidimensional Scaling Author Ingwer Borg
ISBN-10 9783642318481
Release 2012-10-30
Pages 113
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This book introduces MDS as a psychological model and as a data analysis technique for the applied researcher. It also discusses, in detail, how to use two MDS programs, Proxscal (a module of SPSS) and Smacof (an R-package). The book is unique in its orientation on the applied researcher, whose primary interest is in using MDS as a tool to build substantive theories. This is done by emphasizing practical issues (such as evaluating model fit), by presenting ways to enforce theoretical expectations on the MDS solution, and by discussing typical mistakes that MDS users tend to make. The primary audience of this book are psychologists, social scientists, and market researchers. No particular background knowledge is required, beyond a basic knowledge of statistics.

Applied Multidimensional Scaling and Unfolding

Applied Multidimensional Scaling and Unfolding Author Ingwer Borg
ISBN-10 9783319734712
Release 2018-05-16
Pages 122
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This book introduces multidimensional scaling (MDS) and unfolding as data analysis techniques for applied researchers. MDS is used for the analysis of proximity data on a set of objects, representing the data as distances between points in a geometric space (usually of two dimensions). Unfolding is a related method that maps preference data (typically evaluative ratings of different persons on a set of objects) as distances between two sets of points (representing the persons and the objects, resp.). This second edition has been completely revised to reflect new developments and the coverage of unfolding has also been substantially expanded. Intended for applied researchers whose main interests are in using these methods as tools for building substantive theories, it discusses numerous applications (classical and recent), highlights practical issues (such as evaluating model fit), presents ways to enforce theoretical expectations for the scaling solutions, and addresses the typical mistakes that MDS/unfolding users tend to make. Further, it shows how MDS and unfolding can be used in practical research work, primarily by using the smacof package in the R environment but also Proxscal in SPSS. It is a valuable resource for psychologists, social scientists, and market researchers, with a basic understanding of multivariate statistics (such as multiple regression and factor analysis).

Data Science

Data Science Author Francesco Palumbo
ISBN-10 9783319557236
Release 2017-07-04
Pages 342
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This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.

Intelligent Systems for Computer Modelling

Intelligent Systems for Computer Modelling Author Vítězslav Stýskala
ISBN-10 9783319276441
Release 2016-02-13
Pages 246
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This volume of Advances in Intelligent Systems and Computing contains papers presented at the 1st European-Middle Asian Conference on Computer Modelling, EMACOM 2015. This international conference was conceived as a brand new scientific and social event of mutual collaboration between the VSB - Technical University of Ostrava (Ostrava, Czech Republic) and the Kyrgyz National University named after J. Balasagyn (Bishkek, Kyrgyz Republic). The aim of EMACOM 2015 was to present the latest development in the field of computer-aided modelling as an essential aspect of research and development of innovative systems and their applications. The conference showed that together with simulations, various modeling techniques, enabled and encouraged by the rapid development of high-performance computing platforms, are crucial for cost-efficient design, verification, and prototyping of solutions in many diverse industrial fields spanning the whole range from manufacturing, mining, machinery, and automotive industries to infrastructure planning and development, economics, energy, and modern agriculture and food industry.

Facet Theory and the Mapping Sentence

Facet Theory and the Mapping Sentence Author P. Hackett
ISBN-10 9781137345929
Release 2016-04-16
Pages 113
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How do we think about the worlds we live in? The formation of categories of events and objects seems to be a fundamental orientation procedure. Facet theory and its main tool, the mapping sentence, deal with categories of behavior and experience, their interrelationship, and their unification as our worldviews. In this book Hackett reviews philosophical writing along with neuroscientific research and information form other disciplines to provide a context for facet theory and the qualitative developments in this approach. With a variety of examples, the author proposes mapping sentences as a new way of understanding and defining complex behavior.

Modern Multidimensional Scaling

Modern Multidimensional Scaling Author Ingwer Borg
ISBN-10 9781475727111
Release 2013-04-18
Pages 472
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Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distances among points in a geometric space. The main reason for doing this is that one wants a graphical display of the structure of the data, one that is much easier to understand than an array of numbers and, moreover, one that displays the essential information in the data, smoothing out noise. There are numerous varieties of MDS. Some facets for distinguishing among them are the particular type of geometry into which one wants to map the data, the mapping function, the algorithms used to find an optimal data representation, the treatment of statistical error in the models, or the possibility to represent not just one but several similarity matrices at the same time. Other facets relate to the different purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to differences in the data required for the particular models. In this book, we give a fairly comprehensive presentation of MDS. For the reader with applied interests only, the first six chapters of Part I should be sufficient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.

Recommender Systems Handbook

Recommender Systems Handbook Author Francesco Ricci
ISBN-10 9781489976376
Release 2015-11-17
Pages 1003
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This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

Humor at Work in Teams Leadership Negotiations Learning and Health

Humor at Work in Teams  Leadership  Negotiations  Learning and Health Author Tabea Scheel
ISBN-10 9783319656915
Release 2017-09-04
Pages 143
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This book provides a comprehensive review of the state-of-the-art on the adaptive and maladaptive functions of humor. Humor is inescapable in our daily interactions - also at the work place. Affiliative, self-enhancing, self-deprecating and aggressive humor can all occur at work and have unique and sometimes ambiguous effects. The volume presents humor research on five important workplace topics: teams, leadership, negotiation, learning, and health. It combines and integrates research from a range of fields, including work and organizational psychology, social psychology, communication, linguistics and sociology. In highlighting research gaps and stating future research questions, the book provides a sufficient starting point for further research on humor in relation to the aforementioned topics. For practitioners, recommendations are provided specific to each area.

Handbook of Test Development

Handbook of Test Development Author Suzanne Lane
ISBN-10 9781136242564
Release 2015-10-30
Pages 676
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The second edition of the Handbook of Test Development provides graduate students and professionals with an up-to-date, research-oriented guide to the latest developments in the field. Including thirty-two chapters by well-known scholars and practitioners, it is divided into five sections, covering the foundations of test development, content definition, item development, test design and form assembly, and the processes of test administration, documentation, and evaluation. Keenly aware of developments in the field since the publication of the first edition, including changes in technology, the evolution of psychometric theory, and the increased demands for effective tests via educational policy, the editors of this edition include new chapters on assessing noncognitive skills, measuring growth and learning progressions, automated item generation and test assembly, and computerized scoring of constructed responses. The volume also includes expanded coverage of performance testing, validity, fairness, and numerous other topics. Edited by Suzanne Lane, Mark R. Raymond, and Thomas M. Haladyna, The Handbook of Test Development, 2nd edition, is based on the revised Standards for Educational and Psychological Testing, and is appropriate for graduate courses and seminars that deal with test development and usage, professional testing services and credentialing agencies, state and local boards of education, and academic libraries serving these groups.

Independent Random Sampling Methods

Independent Random Sampling Methods Author Luca Martino
ISBN-10 9783319726342
Release 2018-03-31
Pages 280
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This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code. The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the links and interplay between ostensibly diverse techniques.

The Proper Generalized Decomposition for Advanced Numerical Simulations

The Proper Generalized Decomposition for Advanced Numerical Simulations Author Francisco Chinesta
ISBN-10 9783319028651
Release 2013-10-08
Pages 117
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Many problems in scientific computing are intractable with classical numerical techniques. These fail, for example, in the solution of high-dimensional models due to the exponential increase of the number of degrees of freedom. Recently, the authors of this book and their collaborators have developed a novel technique, called Proper Generalized Decomposition (PGD) that has proven to be a significant step forward. The PGD builds by means of a successive enrichment strategy a numerical approximation of the unknown fields in a separated form. Although first introduced and successfully demonstrated in the context of high-dimensional problems, the PGD allows for a completely new approach for addressing more standard problems in science and engineering. Indeed, many challenging problems can be efficiently cast into a multi-dimensional framework, thus opening entirely new solution strategies in the PGD framework. For instance, the material parameters and boundary conditions appearing in a particular mathematical model can be regarded as extra-coordinates of the problem in addition to the usual coordinates such as space and time. In the PGD framework, this enriched model is solved only once to yield a parametric solution that includes all particular solutions for specific values of the parameters. The PGD has now attracted the attention of a large number of research groups worldwide. The present text is the first available book describing the PGD. It provides a very readable and practical introduction that allows the reader to quickly grasp the main features of the method. Throughout the book, the PGD is applied to problems of increasing complexity, and the methodology is illustrated by means of carefully selected numerical examples. Moreover, the reader has free access to the Matlab© software used to generate these examples.

Machine Learning in Medicine Cookbook Three

Machine Learning in Medicine   Cookbook Three Author Ton J. Cleophas
ISBN-10 9783319121635
Release 2014-10-29
Pages 131
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Unique features of the book involve the following. 1.This book is the third volume of a three volume series of cookbooks entitled "Machine Learning in Medicine - Cookbooks One, Two, and Three". No other self-assessment works for the medical and health care community covering the field of machine learning have been published to date. 2. Each chapter of the book can be studied without the need to consult other chapters, and can, for the readership's convenience, be downloaded from the internet. Self-assessment examples are available at 3. An adequate command of machine learning methodologies is a requirement for physicians and other health workers, particularly now, because the amount of medical computer data files currently doubles every 20 months, and, because, soon, it will be impossible for them to take proper data-based health decisions without the help of machine learning. 4. Given the importance of knowledge of machine learning in the medical and health care community, and the current lack of knowledge of it, the readership will consist of any physician and health worker. 5. The book was written in a simple language in order to enhance readability not only for the advanced but also for the novices. 6. The book is multipurpose, it is an introduction for ignorant, a primer for the inexperienced, and a self-assessment handbook for the advanced. 7. The book, was, particularly, written for jaded physicians and any other health care professionals lacking time to read the entire series of three textbooks. 8. Like the other two cookbooks it contains technical descriptions and self-assessment examples of 20 important computer methodologies for medical data analysis, and it, largely, skips the theoretical and mathematical background. 9. Information of theoretical and mathematical background of the methods described are displayed in a "notes" section at the end of each chapter. 10.Unlike traditional statistical methods, the machine learning methodologies are able to analyze big data including thousands of cases and hundreds of variables. 11. The medical and health care community is little aware of the multidimensional nature of current medical data files, and experimental clinical studies are not helpful to that aim either, because these studies, usually, assume that subgroup characteristics are unimportant, as long as the study is randomized. This is, of course, untrue, because any subgroup characteristic may be vital to an individual at risk. 12. To date, except for a three volume introductary series on the subject entitled "Machine Learning in Medicine Part One, Two, and Thee, 2013, Springer Heidelberg Germany" from the same authors, and the current cookbook series, no books on machine learning in medicine have been published. 13. Another unique feature of the cookbooks is that it was jointly written by two authors from different disciplines, one being a clinician/clinical pharmacologist, one being a mathematician/biostatistician. 14. The authors have also jointly been teaching at universities and institutions throughout Europe and the USA for the past 20 years. 15. The authors have managed to cover the field of medical data analysis in a nonmathematical way for the benefit of medical and health workers. 16. The authors already successfully published many statistics textbooks and self-assessment books, e.g., the 67 chapter textbook entitled "Statistics Applied to Clinical Studies 5th Edition, 2012, Springer Heidelberg Germany" with downloads of 62,826 copies. 17. The current cookbook makes use, in addition to SPSS statistical software, of various free calculators from the internet, as well as the Konstanz Information Miner (Knime), a widely approved free machine learning package, and the free Weka Data Mining package from New Zealand. 18. The above software packages with hundreds of nodes, the basic processing units including virtually all of the statistical and data mining methods, can be used not only for data analyses, but also for appropriate data storage. 19. The current cookbook shows, particularly, for those with little affinity to value tables, that data mining in the form of a visualization process is very well feasible, and often more revealing than traditional statistics. 20.The Knime and Weka data miners uses widely available excel data files. 21. In current clinical research prospective cohort studies are increasingly replacing the costly controlled clinical trials, and modern machine learning methodologies like probit and tobit regressions as well as neural networks, Bayesian networks, and support vector machines prove to better fit their analysis than traditional statistical methods do. 22. The current cookbook not only includes concise descriptions of standard machine learning methods, but also of more recent methods like the linear machine learning models using ordinal and loglinear regression. 23. Machine learning tends to increasingly use evolutionary operation methodologies. Also this subject has been covered. 24. All of the methods described have been applied in the authors' own research prior to this publication.

Re activation of Vacant Retail Spaces

Re activation of Vacant Retail Spaces Author Luca Tamini
ISBN-10 9783319708720
Release 2017-11-16
Pages 96
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This book presents an original methodology for analyzing urban retail systems, addressing the strong retail meltdown (increase in closed corner-shops and dead malls) that is severely affecting cities and suburban areas in Europe and the USA. Taking into account both spatial and regulative aspects, it offers a new approach to retailing and retail spaces developed within the urban planning field. The book describes international case studies together with solutions to the problem of vacant retail spaces, and provides a comprehensive toolbox of guidelines useful to local and regional governments facing the problem of retail meltdown. As such, it is of interest to architects, engineers, urban planners, decision-makers and government representatives. It also provides a valuable methodological reference resource for researchers engaged in this particular field of study.

Nonlinear Principal Component Analysis and Its Applications

Nonlinear Principal Component Analysis and Its Applications Author Yuichi Mori
ISBN-10 9789811001598
Release 2016-12-09
Pages 80
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This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement levels data. In the part dealing with the principle, after a brief introduction of ordinary PCA, a PCA for categorical data (nominal and ordinal) is introduced as nonlinear PCA, in which an optimal scaling technique is used to quantify the categorical variables. The alternating least squares (ALS) is the main algorithm in the method. Multiple correspondence analysis (MCA), a special case of nonlinear PCA, is also introduced. All formulations in these methods are integrated in the same manner as matrix operations. Because any measurement levels data can be treated consistently as numerical data and ALS is a very powerful tool for estimations, the methods can be utilized in a variety of fields such as biometrics, econometrics, psychometrics, and sociology. In the applications part of the book, four applications are introduced: variable selection for mixed measurement levels data, sparse MCA, joint dimension reduction and clustering methods for categorical data, and acceleration of ALS computation. The variable selection methods in PCA that originally were developed for numerical data can be applied to any types of measurement levels by using nonlinear PCA. Sparseness and joint dimension reduction and clustering for nonlinear data, the results of recent studies, are extensions obtained by the same matrix operations in nonlinear PCA. Finally, an acceleration algorithm is proposed to reduce the problem of computational cost in the ALS iteration in nonlinear multivariate methods. This book thus presents the usefulness of nonlinear PCA which can be applied to different measurement levels data in diverse fields. As well, it covers the latest topics including the extension of the traditional statistical method, newly proposed nonlinear methods, and computational efficiency in the methods.

Simplicial Global Optimization

Simplicial Global Optimization Author Remigijus Paulavičius
ISBN-10 9781461490937
Release 2013-10-09
Pages 137
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Simplicial Global Optimization is centered on deterministic covering methods partitioning feasible region by simplices. This book looks into the advantages of simplicial partitioning in global optimization through applications where the search space may be significantly reduced while taking into account symmetries of the objective function by setting linear inequality constraints that are managed by initial partitioning. The authors provide an extensive experimental investigation and illustrates the impact of various bounds, types of subdivision, strategies of candidate selection on the performance of algorithms. A comparison of various Lipschitz bounds over simplices and an extension of Lipschitz global optimization with-out the Lipschitz constant to the case of simplicial partitioning is also depicted in this text. Applications benefiting from simplicial partitioning are examined in detail such as nonlinear least squares regression and pile placement optimization in grillage-type foundations. Researchers and engineers will benefit from simplicial partitioning algorithms such as Lipschitz branch and bound, Lipschitz optimization without the Lipschitz constant, heuristic partitioning presented. This book will leave readers inspired to develop simplicial versions of other algorithms for global optimization and even use other non-rectangular partitions for special applications.

Independent Component Analysis of Edge Information for Face Recognition

Independent Component Analysis of Edge Information for Face Recognition Author Kailash J. Karande
ISBN-10 9788132215127
Release 2013-07-15
Pages 81
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The book presents research work on face recognition using edge information as features for face recognition with ICA algorithms. The independent components are extracted from edge information. These independent components are used with classifiers to match the facial images for recognition purpose. In their study, authors have explored Canny and LOG edge detectors as standard edge detection methods. Oriented Laplacian of Gaussian (OLOG) method is explored to extract the edge information with different orientations of Laplacian pyramid. Multiscale wavelet model for edge detection is also proposed to extract edge information. The book provides insights for advance research work in the area of image processing and biometrics.

Multidisciplinary Information Retrieval

Multidisciplinary Information Retrieval Author David Lamas
ISBN-10 9783319129792
Release 2014-10-13
Pages 133
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This book constitutes the proceedings of the 7th International Information Retrieval Facility Conference, IRFC 2014, held in Copenhagen, Denmark, November 2014. The 10 papers presented together with one industry paper were carefully reviewed and selected from 13 submissions. The conference aims at bringing young researchers into contact with the industry at an early stage, emphasizing the applicability of IR solutions to real industry cases and the respective challenges.