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Discriminatory Analysis Nonparametric Discrimination Small Sample Performance
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Book Synopsis Discriminatory Analysis - Nonparametric Discrimination: Small Sample Performance by :
Download or read book Discriminatory Analysis - Nonparametric Discrimination: Small Sample Performance written by and published by . This book was released on 1952 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: A classification procedure is worked out for the following situations: Two large samples, one from each of two populations, have been observed. An individual of unknown origin is to be classified as belonging to the first population if the majority of a specified odd number of individuals closet to the individual in question belong to the first population. This method has optimum properties when the number of closest individuals is permitted to be very large. For certain cases involving multivariate normal distributions with the same covariance matrix, the probabilities of possible misclassification have been computed and compared with those of the discriminant function method.
Book Synopsis Discriminatory Analysis by : Joseph Lawson Hodges
Download or read book Discriminatory Analysis written by Joseph Lawson Hodges and published by . This book was released on 1950 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Discriminatory Analysis by : Evelyn Fix
Download or read book Discriminatory Analysis written by Evelyn Fix and published by . This book was released on 1985 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Lectures on the Nearest Neighbor Method by : Gérard Biau
Download or read book Lectures on the Nearest Neighbor Method written by Gérard Biau and published by Springer. This book was released on 2015-12-08 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods. Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).
Book Synopsis Project Report by : USAF School of Aerospace Medicine
Download or read book Project Report written by USAF School of Aerospace Medicine and published by . This book was released on 1952 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book NASA Technical Note written by and published by . This book was released on 1965 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Elementary Introduction to Statistical Learning Theory by : Sanjeev Kulkarni
Download or read book An Elementary Introduction to Statistical Learning Theory written by Sanjeev Kulkarni and published by John Wiley & Sons. This book was released on 2011-06-09 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory. Explaining these areas at a level and in a way that is not often found in other books on the topic, the authors present the basic theory behind contemporary machine learning and uniquely utilize its foundations as a framework for philosophical thinking about inductive inference. Promoting the fundamental goal of statistical learning, knowing what is achievable and what is not, this book demonstrates the value of a systematic methodology when used along with the needed techniques for evaluating the performance of a learning system. First, an introduction to machine learning is presented that includes brief discussions of applications such as image recognition, speech recognition, medical diagnostics, and statistical arbitrage. To enhance accessibility, two chapters on relevant aspects of probability theory are provided. Subsequent chapters feature coverage of topics such as the pattern recognition problem, optimal Bayes decision rule, the nearest neighbor rule, kernel rules, neural networks, support vector machines, and boosting. Appendices throughout the book explore the relationship between the discussed material and related topics from mathematics, philosophy, psychology, and statistics, drawing insightful connections between problems in these areas and statistical learning theory. All chapters conclude with a summary section, a set of practice questions, and a reference sections that supplies historical notes and additional resources for further study. An Elementary Introduction to Statistical Learning Theory is an excellent book for courses on statistical learning theory, pattern recognition, and machine learning at the upper-undergraduate and graduate levels. It also serves as an introductory reference for researchers and practitioners in the fields of engineering, computer science, philosophy, and cognitive science that would like to further their knowledge of the topic.
Book Synopsis Theory of Decision under Uncertainty by : Itzhak Gilboa
Download or read book Theory of Decision under Uncertainty written by Itzhak Gilboa and published by Cambridge University Press. This book was released on 2009-03-16 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories. It focuses on the meaning of probability, discussing some definitions and surveying their scope of applicability. The behavioral definition of subjective probability serves as a way to present the classical theories, culminating in Savage's theorem. The limitations of this result as a definition of probability lead to two directions - first, similar behavioral definitions of more general theories, such as non-additive probabilities and multiple priors, and second, cognitive derivations based on case-based techniques.
Book Synopsis Analogies and Theories by : Itzhak Gilboa
Download or read book Analogies and Theories written by Itzhak Gilboa and published by OUP Oxford. This book was released on 2015-05-14 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book describes formal models of reasoning that are aimed at capturing the way that economic agents, and decision makers in general think about their environment and make predictions based on their past experience. The focus is on analogies (case-based reasoning) and general theories (rule-based reasoning), and on the interaction between them, as well as between them and Bayesian reasoning. A unified approach allows one to study the dynamics of inductive reasoning in terms of the mode of reasoning that is used to generate predictions.
Book Synopsis Case-Based Approximate Reasoning by : Eyke Hüllermeier
Download or read book Case-Based Approximate Reasoning written by Eyke Hüllermeier and published by Springer Science & Business Media. This book was released on 2007-03-20 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR.
Book Synopsis Technical Documentary Report, SAM-TDR by : USAF School of Aerospace Medicine
Download or read book Technical Documentary Report, SAM-TDR written by USAF School of Aerospace Medicine and published by . This book was released on 1950 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Discriminant Analysis and Statistical Pattern Recognition by : Geoffrey J. McLachlan
Download or read book Discriminant Analysis and Statistical Pattern Recognition written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2005-02-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." –SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.
Book Synopsis Proceedings of the 4th International Conference on Electronics, Biomedical Engineering, and Health Informatics by : Triwiyanto Triwiyanto
Download or read book Proceedings of the 4th International Conference on Electronics, Biomedical Engineering, and Health Informatics written by Triwiyanto Triwiyanto and published by Springer Nature. This book was released on with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Granular Computing in Decision Approximation by : Lech Polkowski
Download or read book Granular Computing in Decision Approximation written by Lech Polkowski and published by Springer. This book was released on 2015-04-06 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusions, the latter introduced and studied within rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k—nearest neighbors and bayesian classifiers. Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook.
Book Synopsis Memory-Based Language Processing by : Walter Daelemans
Download or read book Memory-Based Language Processing written by Walter Daelemans and published by Cambridge University Press. This book was released on 2005-09-01 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memory-based language processing - a machine learning and problem solving method for language technology - is based on the idea that the direct reuse of examples using analogical reasoning is more suited for solving language processing problems than the application of rules extracted from those examples. This book discusses the theory and practice of memory-based language processing, showing its comparative strengths over alternative methods of language modelling. Language is complex, with few generalizations, many sub-regularities and exceptions, and the advantage of memory-based language processing is that it does not abstract away from this valuable low-frequency information. By applying the model to a range of benchmark problems, the authors show that for linguistic areas ranging from phonology to semantics, it produces excellent results. They also describe TiMBL, a software package for memory-based language processing. The first comprehensive overview of the approach, this book will be invaluable for computational linguists, psycholinguists and language engineers.
Book Synopsis Signal Processing for Cognitive Radios by : Sudharman K. Jayaweera
Download or read book Signal Processing for Cognitive Radios written by Sudharman K. Jayaweera and published by John Wiley & Sons. This book was released on 2014-12-16 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines signal processing techniques for cognitive radios. The book is divided into three parts: Part I, is an introduction to cognitive radios and presents a history of the cognitive radio (CR), and introduce their architecture, functionalities, ideal aspects, hardware platforms, and state-of-the-art developments. Dr. Jayaweera also introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Part II of the book, Theoretical Foundations, guides the reader from classical to modern theories on statistical signal processing and inference. The author addresses detection and estimation theory, power spectrum estimation, classification, adaptive algorithms (machine learning), and inference and decision processes. Applications to the signal processing, inference and learning problems encountered in cognitive radios are interspersed throughout with concrete and accessible examples. Part III of the book, Signal Processing in Radios, identifies the key signal processing, inference, and learning tasks to be performed by wideband autonomous cognitive radios. The author provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios.
Book Synopsis Applied Bayesian and Classical Inference by : F. Mosteller
Download or read book Applied Bayesian and Classical Inference written by F. Mosteller and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new version has two additions. First, at the suggestion of Stephen Stigler I we have replaced the Table of Contents by what he calls an Analytic Table of Contents. Following the title of each section or subsection is a description of the content of the section. This material helps the reader in several ways, for example: by giving a synopsis of the book, by explaining where the various data tables are and what they deal with, by telling what theory is described where. We did several distinct full studies for the Federalist papers as well as many minor side studies. Some or all may offer information both to the applied and the theoretical reader. We therefore try to give in this Contents more than the few cryptic words in a section heading to ~peed readers in finding what they want. Seconq, we have prepared an extra chapter dealing with authorship work published from. about 1969 to 1983. Although a chapter cannot compre hensively Gover a field where many books now appear, it can mention most ofthe book-length works and the main thread of authorship' studies published in English. We founq biblical authorship studies so extensive and com plicated that we thought it worthwhile to indicate some papers that would bring out the controversies that are taking place. We hope we have given the flavor of developments over the 15 years mentioned. We have also corrected a few typographical errors.
