Download or read book Around Classification Theory of Models written by Saharon Shelah and published by Springer. This book was released on 2006-12-08 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Classification Theory written by S. Shelah and published by Elsevier. This book was released on 1990-12-06 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this research monograph, the author's work on classification and related topics are presented. This revised edition brings the book up to date with the addition of four new chapters as well as various corrections to the 1978 text.The additional chapters X - XIII present the solution to countable first order T of what the author sees as the main test of the theory. In Chapter X the Dimensional Order Property is introduced and it is shown to be a meaningful dividing line for superstable theories. In Chapter XI there is a proof of the decomposition theorems. Chapter XII is the crux of the matter: there is proof that the negation of the assumption used in Chapter XI implies that in models of T a relation can be defined which orders a large subset of m
Download or read book Classification Theory written by John T. Baldwin and published by Springer. This book was released on 2006-11-14 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Diagnostic Classification Models written by Matthias von Davier and published by Springer Nature. This book was released on 2019-10-11 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification. The handbook also offers applications and special topics and practical guidelines how to plan and conduct research studies with the help of DCMs. Commonly used models in educational measurement and psychometrics typically assume a single latent trait or at best a small number of latent variables that are aimed at describing individual differences in observed behavior. While this allows simple rankings of test takers along one or a few dimensions, it does not provide a detailed picture of strengths and weaknesses when assessing complex cognitive skills. DCMs, on the other hand, allow the evaluation of test taker performance relative to a potentially large number of skill domains. Most diagnostic models provide a binary mastery/non-mastery classification for each of the assumed test taker attributes representing these skill domains. Attribute profiles can be used for formative decisions as well as for summative purposes, for example in a multiple cut-off procedure that requires mastery on at least a certain subset of skills. The number of DCMs discussed in the literature and applied to a variety of assessment data has been increasing over the past decades, and their appeal to researchers and practitioners alike continues to grow. These models have been used in English language assessment, international large scale assessments, and for feedback for practice exams in preparation of college admission testing, just to name a few. Nowadays, technology-based assessments provide increasingly rich data on a multitude of skills and allow collection of data with respect to multiple types of behaviors. Diagnostic models can be understood as an ideal match for these types of data collections to provide more in-depth information about test taker skills and behavioral tendencies.
Download or read book Classification Theory for Abstract Elementary Classes written by Saharon Shelah and published by College Publications. This book was released on 2009 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: An abstract elementary class (AEC) is a class of structures of a fixed vocabulary satisfying some natural closure properties. These classes encompass the normal classes defined in model theory and natural examples arise from mathematical practice, e.g. in algebra not to mention first order and infinitary logics. An AEC is always endowed with a special substructure relation which is not always the obvious one. Abstract elementary classes provide one way out of the cul de sac of the model theory of infinitary languages which arose from over-concentration on syntactic criteria. This is the second volume of a two-volume monograph on abstract elementary classes. It is quite self-contained and deals with three separate issues. The first is the topic of universal classes, i.e. classes of structures of a fixed vocabulary such that a structure belongs to the class if and only if every finitely generated substructure belongs. Then we derive from an assumption on the number of models, the existence of an (almost) good frame. The notion of frame is a natural generalization of the first order concept of superstability to this context. The assumption says that the weak GCH holds for a cardinal $\lambda$, its successor and double successor, and the class is categorical in the first two, and has an intermediate value for the number of models in the third. In particular, we can conclude from this argument the existence of a model in the next cardinal. Lastly we deal with the non-structure part of the topic, that is, getting many non-isomorphic models in the double successor of $ \lambda$ under relevant assumptions, we also deal with almost good frames themselves and some relevant set theory.
Download or read book Introduction to Model Theory written by Philipp Rothmaler and published by CRC Press. This book was released on 2018-12-07 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model theory investigates mathematical structures by means of formal languages. So-called first-order languages have proved particularly useful in this respect. This text introduces the model theory of first-order logic, avoiding syntactical issues not too relevant to model theory. In this spirit, the compactness theorem is proved via the algebraically useful ultrsproduct technique (rather than via the completeness theorem of first-order logic). This leads fairly quickly to algebraic applications, like Malcev's local theorems of group theory and, after a little more preparation, to Hilbert's Nullstellensatz of field theory. Steinitz dimension theory for field extensions is obtained as a special case of a much more general model-theoretic treatment of strongly minimal theories. There is a final chapter on the models of the first-order theory of the integers as an abelian group. Both these topics appear here for the first time in a textbook at the introductory level, and are used to give hints to further reading and to recent developments in the field, such as stability (or classification) theory.
Download or read book Classification Theory Second Edition with a New Introduction written by Saharon Shelah and published by . This book was released on 2023-01-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for readers who have learned about first order logic; Gödel's completeness theorem; the Löwenheim-Skolem theorem; the Tarski-Vaught criterion for being elementary sub-model; and who know naive set theory. A graduate course in model theory will be helpful. The thesis of the book is that we can find worthwhile dividing lines among complete first order theories T; mainly countable. That is, properties dividing them in some sense between understandable and complicated ones. The main test problem is the number of models of T of the infinite cardinal l as a function of l. This culminates in the so-called main gap theorem saying the number is either maximal or quite small in suitable sense. Toward this, other properties are introduced and investigated, such as being stable or being super stable, where can we define dimension and weight, particularly for super stable theories.
Download or read book Model Theory written by C.C. Chang and published by Elsevier. This book was released on 1990-06-12 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the second edition of this book (1977), Model Theory has changed radically, and is now concerned with fields such as classification (or stability) theory, nonstandard analysis, model-theoretic algebra, recursive model theory, abstract model theory, and model theories for a host of nonfirst order logics. Model theoretic methods have also had a major impact on set theory, recursion theory, and proof theory.This new edition has been updated to take account of these changes, while preserving its usefulness as a first textbook in model theory. Whole new sections have been added, as well as new exercises and references. A number of updates, improvements and corrections have been made to the main text.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Around Classification Theory written by Saharon Shelal and published by . This book was released on 1986 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Model Based Clustering and Classification for Data Science written by Charles Bouveyron and published by Cambridge University Press. This book was released on 2019-07-25 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Download or read book CLASSIFICATION THEORY DIMENSIONAL ORDER PROPERTY AND PAIRS OF MODELS COUNTABLE MODELS OF OMEGA STABLE THEORIES written by Élisabeth Bouscaren and published by . This book was released on 1985 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTRODUCTION GENERALE. PREMIERE PARTIE. PROPRIETE D'ORDRE DIMENSIONNELLE ET PAIRES DE MODELES. DEUXIEME PARTIE. MODELES DENOMBRABLES DES THEORIES OMEGA -STABLES
Download or read book Classification of countable models of complete theories art 2 written by Sergey Sudoplatov and published by Litres. This book was released on 2022-01-29 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is the second part of the monograph “Classification of countable models of complete theories” consisting of two parts. In the book, generic Ehrenfeucht theories and realizations of Rudin–Keisler preorders are considered as well as a solution of the Goncharov–Millar problem on the existence of Ehrenfeucht theories with countable models which are not almost homogeneous, stable Ehrenfeucht theories solving the Lachlan problem, hypergraphs of prime models, distributions of countable models of small theories, and distributions of countable models of theories with continuum many types.The book is intended for specialists interested in Mathematical Logic.
Download or read book Machine Learning Models and Algorithms for Big Data Classification written by Shan Suthaharan and published by Springer. This book was released on 2015-10-20 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.
Download or read book Classification of countable models of complete theories art 1 written by Sergey Sudoplatov and published by Litres. This book was released on 2022-01-29 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is the first part of the monograph “Classification of countable models of complete theories” consisting of two parts. In the monograph, a classification of countable models of complete theories with respect to two basic characteristics (Rudin–Keisler preorders and distribution functions for numbers of limit models) is presented and applied to the most important classes of countable theories such as the class of Ehrenfeucht theories (i. e., complete first-order theories with finitely many but more than one pairwise non-isomorphic countable models), the class of small theories (i. e., complete first-order theories with countably many types), and the class of countable first-order theories with continuum many types. For realizations of basic characteristics of countable complete theories, syntactic generic constructions, generalizing the Jonsson–Fraïssé construction and the Hrushovski construction, are presented. Using these constructions a solution of the Goncharov–Millar problem (on the existence of Ehrenfeucht theories with countable models which are not almost homogeneous) is described. Modifying the Hrushovski–Herwig generic construction, a solution of the Lachlan problem on the existence of stable Ehrenfeucht theories is shown. In the first part, a characterization of Ehrenfeuchtness, properties of Ehrenfeucht theories, generic constructions, and algebras for distributions of binary semi-isolating formulas of a complete theory are considered.The book is intended for specialists interested in Mathematical Logic.
Download or read book Set Theoretic Models for Classification and Retrieval written by Richard Jernigan and published by . This book was released on 1964 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: The appropriateness of lattice models as analogues of classification and retrieval systems is analyzed. Models considered include simple distributive lattices, and implicative and subtractive lattices. A particular topological model is also considered. It is shown that any set of topological axioms will be reducible to a Boolean algebra when applied to finite spaces. (Author).
Download or read book Understanding and Evaluating Research written by Sue L. T. McGregor and published by SAGE Publications. This book was released on 2017-10-25 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding and Evaluating Research: A Critical Guide shows students how to be critical consumers of research and to appreciate the power of methodology as it shapes the research question, the use of theory in the study, the methods used, and how the outcomes are reported. The book starts with what it means to be a critical and uncritical reader of research, followed by a detailed chapter on methodology, and then proceeds to a discussion of each component of a research article as it is informed by the methodology. The book encourages readers to select an article from their discipline, learning along the way how to assess each component of the article and come to a judgment of its rigor or quality as a scholarly report.
