Pattern Classification Using Ensemble Methods

This concise yet comprehensive textbook examines political, social, and cultural developments in the Soviet Union and the post-Soviet period. It begins by identifying the social tensions and political inconsistencies that spurred radical change in Russia's government, from the turn of the century to the revolution of 1917. Peter Kenez presents this revolution as a crisis of authority that the creation of the Soviet Union resolved. The text traces the progress of the Soviet Union through the 1920s, the years of the New Economic Policies, and into the Stalinist order. It illustrates how post-Stalin Soviet leaders struggled to find ways to rule the country without using Stalin's methods - but also without openly repudiating the past - and to negotiate a peaceful but antipathetic coexistence with the capitalist West. This updated third edition includes substantial new material, discussing the challenges Russia currently faces in the era of Putin.

This graduate-level text gives a self-contained exposition of fundamental topics in equilibrium and nonequilibrium statistical thermodynamics. The text follows a balanced approach between the macroscopic (thermodynamic) and microscopic (statistical) points of view. The first half of the book deals with equilibrium thermodynamics and statistical mechanics. In addition to standard subjects, the reader will find a detailed account of broken symmetries, critical phenomena and the renormalization group, as well as an introduction to numerical methods. The second half of the book is devoted to nonequilibrium phenomena, first following a macroscopic approach, with hydrodynamics as an important example. Kinetic theory receives a thorough treatment through analysis of the Boltzmann-Lorentz model and the Boltzmann equation. The book concludes with general nonequilibrium methods such as linear response, projection method and the Langevin and Fokker-Planck equations, including numerical simulation

Historically, naturalists who proposed theories of evolution, including Darwin and Wallace, did so in order to explain the apparent relationship of natural classification. This book begins by exploring the intimate historical relationship between patterns of classification and patterns of phylogeny. However, it is a circular argument to use the data for classification. Alec Panchen presents other evidence for evolution in the form of a historically based but rigorously logical argument. This is followed by a history of methods of classification and phylogeny reconstruction including current mathematical and molecular techniques. The author makes the important claim that if the hierarchical pattern of classification is a real phenomenon, then biology is unique as a science in making taxonomic statements. This conclusion is reached by way of historical reviews of theories of evolutionary mechanism and the philosophy of science as applied to biology. The book is addressed to biologists, p

Connecting theory with real-life applications, this is the first ever textbook to equip students with a comprehensive knowledge of all the key concepts in bionanotechnology. By bridging the interdisciplinary gap from which bionanotechnology emerged, it provides a systematic introduction to the subject, accessible to students from a wide variety of backgrounds. Topics range from nanomaterial preparation, properties and biofunctionalisation, and analytical methods used in bionanotechnology, to bioinspired and DNA nanotechnology, and applications in biosensing, medicine and tissue engineering. Throughout the book, features such as 'Back to basics' and 'Research report' boxes enable students to build a strong theoretical knowledge and to link this to practical applications and up-to-date research. With over 200 detailed, full-colour illustrations and more than 100 end-of-chapter problems, this is an essential guide to bionanotechnology for any student studying this exciting, fast-developin

Plant remains can preserve a critical part of history of life on Earth. While telling the fascinating evolutionary story of plants and vegetation across the last 500 million years, this book also crucially offers non-specialists a practical guide to studying, dealing with and interpreting plant fossils. It shows how various techniques can be used to reveal the secrets of plant fossils and how to identify common types, such as compressions and impressions. Incorporating the concepts of evolutionary floras, this second edition includes revised data on all main plant groups, the latest approaches to naming plant fossils using fossil-taxa and techniques such as tomography. With extensive illustrations of plant fossils and living plants, the book encourages readers to think of fossils as once-living organisms. It is written for students on introductory or intermediate courses in palaeobotany, palaeontology, plant evolutionary biology and plant science, and for amateurs interested in studyin

Scientists have a choice concerning what role they should play in political debates and policy formation, particularly in terms of how they present their research. This book is about understanding this choice, what considerations are important to think about when deciding, and the consequences of such choices for the individual scientist and the broader scientific enterprise. Rather than prescribing what course of action each scientist ought to take, the book aims to identify a range of options for individual scientists to consider in making their own judgments about how they would like to position themselves in relation to policy and politics. Using examples from a range of scientific controversies and thought-provoking analogies from other walks of life, The Honest Broker challenges us all - scientists, politicians and citizens - to think carefully about how best science can contribute to policy-making and a healthy democracy.

Kant is the central figure of modern philosophy. He sought to rebuild philosophy from the ground up, and he succeeded in permanently changing its problems and methods. This revised edition of the Prolegomena, which is the best introduction to the theoretical side of his philosophy, presents his thought clearly by paying careful attention to his original language. Also included are selections from the Critique of Pure Reason, which fill out and explicate some of Kant's central arguments (including famous sections of the Schematism and Analogies), and in which Kant himself explains his special terminology. The first reviews of the Critique, to which Kant responded in the Prolegomena, are included in this revised edition. The volume is completed by a historical and philosophical introduction, explanatory notes, a chronology, and a guide to further reading.

本書是一部系統性探討海洋與沿岸波浪的專業著作，兼顧物理意義與統計分析，適合研究所學生、研究人員與工程實務者閱讀。內容從觀測技術談起，介紹現地量測與遙測方法，並逐步建立描述波浪的參數與統計架構。書中詳述線性波理論在外海與近岸水域的應用，說明波浪在不同水深與地形條件下的行為差異，並深入介紹 SWAN 波浪模式，協助讀者理解現代數值模擬在工程與研究中的角色。全書結構嚴謹、插圖清楚，是理解風生波浪與海岸波動不可或缺的參考書。Waves in Oceanic and Coastal Waters describes the observation, analysis and prediction of wind-generated waves in the open ocean, in shelf seas, and in coastal regions with islands, channels, tidal flats and inlets, estuaries, fjords and lagoons. Most of this richly illustrated book is devoted to the physical aspects of waves. After introducing observation techniques for waves, both at sea and from space, the book defines the parameters that characterise waves. Using basic statistical and physical concepts, the author discusses the prediction of waves in oceanic and coastal waters, first in terms of generalised observations, and then in terms of the more theoretical framework of the spectral energy balance. He gives the results of established theories and also the direction in wh

Things which we regard as the everyday objects of consumption (and hence re-purchase), and essential to any decent, civilised lifestyle, have not always been so: in former times, everyday objects would have passed from one generation to another, without anyone dreaming of acquiring new ones. How, therefore, have people in the modern world become 'prisoners of objects', as Rousseau put it? The celebrated French cultural historian Daniel Roche answers this fundamental question using insights from economics, politics, demography and geography, as well as his own extensive historical knowledge. Professor Roche places familiar objects and commodities - houses, clothes, water - in their wider historical and anthropological contexts, and explores the origins of some of the daily furnishings of modern life. A History of Everyday Things is a pioneering essay that sheds light on the origins of the consumer society and its social and political repercussions, and thereby the birth of the modern w

The classification of stars into their various types is one of the fundamental areas of astronomy. This book is a comprehensive handbook on the tools, methods and results of stellar taxonomy. Although this subject is firmly rooted in classical astronomy, vast improvements in observational techniques have transformed the subject and greatly broadened the wavelength regions available for study. The first six chapters describe modern methods of spectroscopic and photometric classification. The remaining nine chapters describe particular families of stars, progressing from the hottest to the coolest. Within each category a description is given of the normal type and all the peculiar stars. Throughout the emphasis is on the phenomenology of classification, rather than the underlying astrophysics. Both authors have devoted themselves to developing the international centre for stellar data at Strasbourg, which uniquely qualifies them to write this definitive handbook for professional astronom

This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.

In recent years cosmologists have advanced from largely qualitative models of the Universe to precision modelling using Bayesian methods, in order to determine the properties of the Universe to high accuracy. This timely book is the only comprehensive introduction to the use of Bayesian methods in cosmological studies, and is an essential reference for graduate students and researchers in cosmology, astrophysics and applied statistics. The first part of the book focuses on methodology, setting the basic foundations and giving a detailed description of techniques. It covers topics including the estimation of parameters, Bayesian model comparison, and separation of signals. The second part explores a diverse range of applications, from the detection of astronomical sources (including through gravitational waves), to cosmic microwave background analysis and the quantification and classification of galaxy properties. Contributions from 24 highly regarded cosmologists and statisticians make

Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target recognition, biometric recognition and optical character recognition. The design, analysis and use of correlation pattern recognition algorithms requires background information, including linear systems theory, random variables and processes, matrix/vector methods, detection and estimation theory, digital signal processing and optical processing. This book provides a needed review of this diverse background material and develops the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. It shows both digital and optical implementations. It also contains technology presented by the team that developed it and includes case studies of significant interest, such as face and fingerprint recognition. Suitable for graduate students taking courses in pattern recognition theory, whilst reaching technical

The Berliner Ensemble was founded by Bertolt Brecht and his wife Helene Weigel in 1949. The company soon gained international prominence, and its productions and philosophy influenced the work of theatre-makers around the world. David Barnett's book is the first study of the company in any language. Based on extensive archival research, it uncovers Brecht's working methods and those of the company's most important directors after his death. The book considers the boon and burden of Brecht's legacy, and provides new insights into battles waged behind the scenes for the preservation of the Brechtian tradition. The Berliner Ensemble was also the German Democratic Republic's most prestigious cultural export, attracting attention from the highest circles of government, and from the Stasi, before it privatised itself after German reunification in 1990. Barnett pieces together a complex history that sheds light on both the company's groundbreaking productions and their turbulent times.

Modern biological classification is based on the system developed by Linnaeus, and interpreted by Darwin as representing the tree of life. But despite its widespread acceptance, the evolutionary interpretation has some problems and limitations. This comprehensive book provides a single resource for understanding all the main philosophical issues and controversies about biological classification. It surveys the history of biological classification from Aristotle to contemporary phylogenetics and shows how modern biological classification has developed and changed over time. Readers will also be able to see how biological classification is in part a consequence of human psychology, language development and culture. The book will be valuable for student readers and others interested in a range of topics in philosophy and biology.

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for

This book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Research on pattern classification with binary-output networks is surveyed, including a discussion of the relevance of the Vapnik–Chervonenkis dimension, and calculating estimates of the dimension for several neural network models. A model of classification by real-output networks is developed, and the usefulness of classification with a 'large margin' is demonstrated. The authors explain the role of scale-sensitive versions of the Vapnik–Chervonenkis dimension in large margin classification, and in real prediction. They also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient constructive learning algorithms. The book is self-contained and is intended to be accessible to researchers and gradua

This book provides a comprehensive review of optical pattern recognition, covering theoretical aspects as well as details of practical implementations and signal processing techniques. The first chapter is devoted to pattern recognition performed with optical correlators. Later chapters discuss approaches based on neural networks, wavelet transforms and the fractional Fourier transform. The book also covers nonlinear filter methods and optical-electronic hybrid systems. The final part of the book deals with the devices and materials employed in modern systems, such as photorefractive crystals, microlasers, and liquid crystal spatial light modulators. The book gives many examples of working systems that integrate optics, electronics and computers, and it covers a range of developments from mathematical theories to novel optical materials. It will be of great interest to graduate students and researchers in optical engineering and machine vision.

The predictability of the physical arrangement of plants, at whatever scale it is viewed, is referred to as their spatial pattern. Spatial pattern is a crucial aspect of vegetation which has important implications not only for the plants themselves, but also for other organisms which interact with plants, such as herbivores and pollinators, or those animals for which plants provide a habitat. This book describes and evaluates methods for detecting and quantifying a variety of characteristics of spatial pattern. As well as discussing the concepts on which these techniques are based, examples from real field studies and worked examples are included, which, together with numerous line figures, help guide the reader through the text. The result is a book that will be of value to graduate students and research workers in the fields of vegetation science, conservation biology and applied ecology.

Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This 1997 book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

Quantitative Methods in Archaeology Using R is the first hands-on guide to using the R statistical computing system written specifically for archaeologists. It shows how to use the system to analyze many types of archaeological data. Part I includes tutorials on R, with applications to real archaeological data showing how to compute descriptive statistics, create tables, and produce a wide variety of charts and graphs. Part II addresses the major multivariate approaches used by archaeologists, including multiple regression (and the generalized linear model); multiple analysis of variance and discriminant analysis; principal components analysis; correspondence analysis; distances and scaling; and cluster analysis. Part III covers specialized topics in archaeology, including intra-site spatial analysis, seriation, and assemblage diversity.

Qualitative Comparative Analysis (QCA) and other set-theoretic methods distinguish themselves from other approaches to the study of social phenomena by using sets and the search for set relations. In virtually all social science fields, statements about social phenomena can be framed in terms of set relations, and using set-theoretic methods to investigate these statements is therefore highly valuable. This book guides readers through the basic principles of set theory and then on to the applied practices of QCA. It provides a thorough understanding of basic and advanced issues in set-theoretic methods together with tricks of the trade, software handling and exercises. Most arguments are introduced using examples from existing research. The use of QCA is increasing rapidly and the application of set-theory is both fruitful and still widely misunderstood in current empirical comparative social research. This book provides the comprehensive guide to these methods for researchers across t

This book is devoted to some mathematical methods that arise in two domains of artificial intelligence: neural networks and qualitative physics. Professor Aubin makes use of control and viability theory in neural networks and cognitive systems, regarded as dynamical systems controlled by synaptic matrices, and set-valued analysis that plays a natural and crucial role in qualitative analysis and simulation. This allows many examples of neural networks to be presented in a unified way. In addition, several results on the control of linear and nonlinear systems are used to obtain a 'learning algorithm' of pattern classification problems, such as the back-propagation formula, as well as learning algorithms of feedback regulation laws of solutions to control systems subject to state constraints. This book will be of value to anyone with an interest in neural networks and cognitive systems.

This 1997 work explores the role of probabilistic methods for solving combinatorial problems. These methods not only provide the means of efficiently using such notions as characteristic and generating functions, the moment method and so on but also let us use the powerful technique of limit theorems. The basic objects under investigation are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these specify the probabilistic setting of Sachkov's general combinatorial scheme. The author pays special attention to using probabilistic methods to obtain asymptotic formulae that are difficult to derive using combinatorial methods. This was an important book, describing many ideas not previously available in English; the author has taken the chance to rewrite parts of the text and refresh the references where appropriate.

Where does the particular form or configuration of a pattern come from, and how is it propagated from pattern to pattern? Templets and the Explanation of Complex Patterns provides a natural language for analysing such questions. Using it, the organisational forces that underlie the fabrication of any pattern can be divided into two classes. First, there are the 'universal laws' of pattern assembly, the configurational rules and constraints inherent within the fabric of the pattern elements themselves. Second, there are the 'templets' - external, situational constraints imposed on the pattern elements. From the perspective of templeting, simple patterns can be directly contrasted with complex patterns: the former are completely determined by their universal laws, whereas the latter also require extensive templets. Natural patterns range along the entire spectrum from simple to complex, and the most complex of these include both random patterns and many biological patterns.

This book, first published in 2000, addresses the fundamental linguistic question of how the perceived world is expressed through systems of nominal classification that are grammatically encoded in various languages. A team of leading international scholars reviews the whole spectrum of nominal classification, from gender systems through to numeral classifiers, providing cutting-edge theoretical interpretations and empirical case studies based on a wide range of languages. The volume presents ideas about the problems of classification, advances theory by proposing typological categories and clarifies the interface between anthropological and grammatical work. Focusing on systems that have a conceptual-semantic basis, the contributors reflect and represent approaches in nominal classification research. This invaluable reference work will appeal to linguists, anthropologists and psychologists alike, as well as specialists in languages as diverse as Australian, Amazonian, Mayan and Japane

Classifications are central to archaeology. Yet the theoretical literature on the subject, both in archaeology and the philosophy of science, bears very little relationship to what actually occurs in practice. This problem has long interested William Adams, a field archaeologist, and Ernest Adams, a philosopher of science, who describe their book as an ethnography of archaeological classification. It is a study of the various ways in which field archaeologists set about making and using classifications to meet a variety of practical needs. The authors first discuss how humans form concepts. They then describe and analyse in detail a specific example of an archaeological classification, and go on to consider what theoretical generalizations can be derived from the study of actual in-use classifications. Throughout the book, they stress the importance of having a clearly defined purpose and practical procedures when developing and applying classifications.

This study aims to resolve the century-old debate about the nature of Australian aboriginal societies and the comparability of their structures with the structures of other tribal and kinship-based societies. It begins with a critical evaluation and refutation of the claims that Australians are 'ignorant of physical paternity' and therefore cannot have systems of kin classification. Professor Scheffler then demonstrates that systems of kin classification are a common feature of Australian languages and that, contrary to the theory proposed by A. R. Radcliffe-Brown and others, variation in the rules of interkin marriage does not account for variation in systems of kin classification. This was the first monographic treatment of the subject since Radcliffe-Brown's classic work, The Social Organization of the Australian Tribes, published in 1931, and is much more comprehensive and synthetic in its coverage of the range of variation in Australian systems of kin classification. It applies th

The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology.

Cowan and Steel's Manual has for many years had an essential role in every laboratory of microbiology and bacteriology. This substantially revised new edition, which is modelled on the successful pattern established in the previous two editions, has been fully updated and is suitable for all bacteriological laboratories using traditional diagnostic methods. It is essentially a practical manual with up-to-date contributions and key references by experts to the diagnostic characteristics of the bacteria likely to be encountered in public health and hospital microbiology laboratories, as well as in medical and veterinary practice. This edition contains new sections on rapid and mechanised test methods, and on the laboratory applications of computer theory and practice to the identification of bacteria. As in previous editions, the importance of laboratory quality control and proficiency procedures are emphasised. The Appendices give details of the laboratory methods and media for all the

This work provides a lucid and rigorous account of the foundations of modern algebraic geometry. The authors have confined themselves to fundamental concepts and geometrical methods, and do not give detailed developments of geometrical properties but geometrical meaning has been emphasised throughout. Volume 2 gives an account of the principal methods used in developing a theory of algebraic varieties in spaces of n dimensions. Applications of these methods are also given to some of the more important varieties which occur in projective geometry. The ground field is without characteristic. Since geometry over any field without characteristic conforms to the general pattern of geometry over the field of complex numbers, a sound algebraic basis for classical geometry is provided. The other two volumes of Hodge and Pedoe's classic work are also available. Together, these books give an insight into algebraic geometry that is unique and unsurpassed.

A polarised variety is a modern generalization of the notion of a variety in classical algebraic geometry. It consists of a pair: the algebraic variety itself, together with an ample line bundle on it. Using techniques from abstract algebraic geometry that have been developed over recent decades, Professor Fujita develops classification theories of such pairs using invariants that are polarised higher-dimensional versions of the genus of algebraic curves. The heart of the book is the theory of D-genus and sectional genus developed by the author, but numerous related topics are discussed or surveyed. Proofs are given in full in the central part of the development, but background and technical results are sometimes just sketched when the details are not essential for understanding the key ideas. Readers are assumed to have some background in algebraic geometry, including sheaf cohomology, and for them this work will provide an illustration of the power of modern abstract techniques appli

Ecologists are making increasing use of computer methods in analyzing ecological data on plant and animal communities. Ecological problems naturally involve numerous variables and numerous individuals or samples. Multivariate techniques permit the summary of large, complex sets of data and provide the means to tackle many problems that cannot be investigated experimentally because of practical restraints. Ecologists are thus enabled to group similar species and similar sample sites together, and to generate hypotheses about environmental and historical factors that affect the communities. This timely book presents a full critical description of three methodologies - direct gradient analysis, ordination, and classification - from both theoretical and practical viewpoints. Both traditional and new methods are presented. Using a wide range of illustrative examples, Hugh Gauch provides an up-to-date synthesis of this field, which will be of interest to advanced students and ecologists. The

Voltaire's correspondence has been described as his 'greatest masterpiece' – but if it is, it is also his least studied. One of the most prodigious correspondences in Western literature, it poses significant interpretative challenges to the critic and reader alike. Considered individually, the letters present a series of complex, subtle, and playful literary performances; taken together, they constitute a formidable, and even forbidding, ensemble. How can modern readers even attempt to understand such an imposing work? This Element addresses this question through the use of digital reading methods and resources that enhance our understanding of this complex literary object and its relationship to Voltaire's more canonical literary output, and indeed to the Enlightenment world at large. Nicholas Cronk and Glenn Roe provide scholars and students with new pathways into this particular corpus, using tools and approaches that can then be applied to correspondences and life-writing texts in

This new edition of a foundational text presents a contemporary review of cladistics, as applied to biological classification. It provides a comprehensive account of the past fifty years of discussion on the relationship between classification, phylogeny and evolution. It covers cladistics in the era of molecular data, detailing new advances and ideas that have emerged over the last twenty-five years. Written in an accessible style by internationally renowned authors in the field, readers are straightforwardly guided through fundamental principles and terminology. Simple worked examples and easy-to-understand diagrams also help readers navigate complex problems that have perplexed scientists for centuries. This practical guide is an essential addition for advanced undergraduates, postgraduates and researchers in taxonomy, systematics, comparative biology, evolutionary biology and molecular biology.

This concise, plain-language guide for senior undergraduates and graduate students aims to develop intuition, practical skills and an understanding of the framework of numerical methods for the physical sciences and engineering. It provides accessible self-contained explanations of mathematical principles, avoiding intimidating formal proofs. Worked examples and targeted exercises enable the student to master the realities of using numerical techniques for common needs such as solution of ordinary and partial differential equations, fitting experimental data, and simulation using particle and Monte Carlo methods. Topics are carefully selected and structured to build understanding, and illustrate key principles such as: accuracy, stability, order of convergence, iterative refinement, and computational effort estimation. Enrichment sections and in-depth footnotes form a springboard to more advanced material and provide additional background. Whether used for self-study, or as the basis o

The field of machine learning has matured to the point where many sophisticated learning approaches can be applied to practical applications. Thus it is of critical importance that researchers have the proper tools to evaluate learning approaches and understand the underlying issues. This book examines various aspects of the evaluation process with an emphasis on classification algorithms. The authors describe several techniques for classifier performance assessment, error estimation and resampling, obtaining statistical significance as well as selecting appropriate domains for evaluation. They also present a unified evaluation framework and highlight how different components of evaluation are both significantly interrelated and interdependent. The techniques presented in the book are illustrated using R and WEKA, facilitating better practical insight as well as implementation. Aimed at researchers in the theory and applications of machine learning, this book offers a solid basis for c

The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discov

Faced with a single neuroradiological image of an unknown patient, how confident would you be to make a differential diagnosis? Despite advanced imaging techniques, a confident diagnosis also requires knowledge of the patient's age, clinical data and the lesion location. Pattern Recognition Neuroradiology provides the tools you will need to arrive at the correct diagnosis or a reasonable differential diagnosis. This user-friendly book includes basic information often omitted from other texts: a practical method of image analysis, sample dictation templates and didactic information regarding lesions/diseases in a concise outline form. Image galleries show more than 700 high quality representative examples of the diseases discussed. Whether you are a trainee encountering some of these conditions for the first time or a resident trying to develop a reliable system of image analysis, Pattern Recognition Neuroradiology is an invaluable diagnostic resource.