List of the Top 9 classification theory you can buy in 2022
When you want to find classification theory, you may need to consider between many choices. Finding the best classification theory is not an easy task. In this post, we create a very short list about top 9 the best classification theory for you. You can check detail product features, product specifications and also our voting for each product. Let’s start with following top 9 classification theory:
1. Classification Theory for Abstract Elementary Classes: Volume 2 (Studies in Logic: Mathematical Logic and Foundations)
Feature
Used Book in Good ConditionDescription
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.2. Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
Description
Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting. This book presents many important techniques for building powerful, robust models and quantifying their expected behavior when put to work in your application.
Considerable attention is given to information theory, especially as it relates to discovering and exploiting relationships between variables employed by your models. This presentation of an often confusing subject avoids advanced mathematics, focusing instead on concepts easily understood by those with modest background in mathematics.
All algorithms include an intuitive explanation of operation, essential equations, references to more rigorous theory, and commented C++ source code. Many of these techniques are recent developments, still not in widespread use. Others are standard algorithms given a fresh look. In every case, the emphasis is on practical applicability, with all code written in such a way that it can easily be included in any program.
- Compute entropy to detect problematic predictors
- Improve numeric predictions using constrained and unconstrained combinations, variance-weighted interpolation, and kernel-regression smoothing
- Carry out classification decisions using Borda counts, MinMax and MaxMin rules, union and intersection rules, logistic regression, selection by local accuracy, maximization of the fuzzy integral, and pairwise coupling
- Harness information-theoretic techniques to rapidly screen large numbers of candidate predictors, identifying those that are especially promising
- Use Monte-Carlo permutation methods to assess the role of good luck in performance results
- Compute confidence and tolerance intervals for predictions, as well as confidence levels for classification decisions
Who This Book is For
Anyone who creates prediction or classification models will find a wealth of useful algorithms in this book. Although all code examples are written in C++, the algorithms are described in sufficient detail that they can easily be programmed in any language.
3. Classification Theory of Algebraic Varieties and Compact Complex Spaces (Lecture Notes in Mathematics)
4. A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)
Description
A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.5. Gauge Theories of Gravitation: A Reader With Commentaries (Classification of Gauge Theories of Gravity)
Description
In the last five decades, the gauge approach to gravity has represented a research area of increasing importance for our understanding of the physics of fundamental interactions. A full clarification of the gauge dynamics of gravity is expected to be the last missing link to the hidden structure of a consistent unification of all the fundamental interactions, based on the gauge principle. The aim of the present reprint volume, with commentaries by Milutin Blagojevic and Friedrich W Hehl, is to introduce graduate and advanced undergraduate students of theoretical or mathematical physics, or any other interested researcher, to the field of classical gauge theories of gravity.This is not just an ordinary reprint volume; it is a guide to the literature on gauge theories of gravity. The reader is encouraged first to study the introductory commentaries and to become familiar with the basic content of the reprints and related ideas, then he/she can choose to read a specific reprint or reprints, and after that he/she should return again to the text and explore the additional literature, etc. The interaction is intended to be more complex than just starting with commentaries and ending with reprints.6. The Theory and Practice of the Dewey Decimal Classification System (Chandos Information Professional Series)
Description
The Dewey Decimal Classification system (DDC) is the worlds most popular library classification system. The 23rd edition of the DDC was published in 2011. This second edition of The Theory and Practice of the Dewey Decimal Classification System examines the history, management and technical aspects of the DDC up to its latest edition. The book places emphasis on explaining the structure and number building techniques in the DDC and reviews all aspects of subject analysis and number building by the most recent version of the DDC. A history of, and introduction to, the DDC is followed by subject analysis and locating class numbers, chapters covering use of the tables and subdivisions therein, multiple synthesis, and using the relative index. In the appendix, a number of academically-interesting questions are identified and answered.- Provides a comprehensive chronology of the DDC from its inception in 1876, to the present day
- Describes the governance, revision machinery and updating process
- Gives a table of all editors of the DDC
7. Classification and Regression Trees (Wadsworth Statistics/Probability)
Feature
Chapman and Hall CRCDescription
The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.8. Measurement Theory and Applications for the Social Sciences (Methodology in the Social Sciences)
Description
Which types of validity evidence should be considered when determining whether a scale is appropriate for a given measurement situation? What about reliability evidence? Using clear explanations illustrated by examples from across the social and behavioral sciences, this engaging text prepares students to make effective decisions about the selection, administration, scoring, interpretation, and development of measurement instruments. Coverage includes the essential measurement topics of scale development, item writing and analysis, and reliability and validity, as well as more advanced topics such as exploratory and confirmatory factor analysis, item response theory, diagnostic classification models, test bias and fairness, standard setting, and equating. End-of-chapter exercises (with answers) emphasize both computations and conceptual understanding to encourage readers to think critically about the material.
9. Character Strengths and Virtues: A Handbook and Classification
Description
"Character" has become a front-and-center topic in contemporary discourse, but this term does not have a fixed meaning. Character may be simply defined by what someone does not do, but a more active and thorough definition is necessary, one that addresses certain vital questions. Is character a singular characteristic of an individual, or is it composed of different aspects? Does character--however we define it--exist in degrees, or is it simply something one happens to have? How can character be developed? Can it be learned? Relatedly, can it be taught, and who might be the most effective teacher? What roles are played by family, schools, the media, religion, and the larger culture? This groundbreaking handbook of character strengths and virtues is the first progress report from a prestigious group of researchers who have undertaken the systematic classification and measurement of widely valued positive traits. They approach good character in terms of separate strengths-authenticity, persistence, kindness, gratitude, hope, humor, and so on-each of which exists in degrees.Character Strengths and Virtues classifies twenty-four specific strengths under six broad virtues that consistently emerge across history and culture: wisdom, courage, humanity, justice, temperance, and transcendence. Each strength is thoroughly examined in its own chapter, with special attention to its meaning, explanation, measurement, causes, correlates, consequences, and development across the life span, as well as to strategies for its deliberate cultivation. This book demands the attention of anyone interested in psychology and what it can teach about the good life.
Recent Comments