Statistical Methods of Discrimination and Classification
Statistical Methods of Discrimination and Classification

Author: Sung C. Choi

Publisher: Elsevier

Published: 2014-05-17

Total Pages: 145

ISBN-13: 1483190986

DOWNLOAD EBOOK

Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a collection of papers that tackles the multivariate problems of discriminating and classifying subjects into exclusive population. The book presents 13 papers that cover that advancement in the statistical procedure of discriminating and classifying. The studies in the text primarily focus on various methods of discriminating and classifying variables, such as multiple discriminant analysis in the presence of mixed continuous and categorical data; choice of the smoothing parameter and efficiency of k-nearest neighbor classification; and assessing the performance of an allocation rule. The book will be of great use to researchers and practitioners of wide array of scientific disciplines, including engineering, psychology, biology, and physics.

Discrimination and Classification
Discrimination and Classification

Author: David J. Hand

Publisher:

Published: 1981-11-04

Total Pages: 240

ISBN-13:

DOWNLOAD EBOOK

Distribution-free methods; Parameterized distributions; Linear discriminant functions; Discrete variables; Variable selection; Cluster analysis; Miscellaneous topics.

Statistical Pattern Recognition
Statistical Pattern Recognition

Author: Andrew R. Webb

Publisher: Newnes

Published: 1999

Total Pages: 476

ISBN-13: 9780340741641

DOWNLOAD EBOOK

"This book provides an introduction to statistical pattern recognition theory and techniques. Most of the material presented in this book is concerned with discrimination and classification and has been drawn from a wide range of literature including that of engineering, statistics, computer science and the social sciences. This book is an attempt to provide a concise volume containing descriptions of many of the most useful of today's pattern processing techniques including many of the recent advances in nonparametric approaches to discrimination developed in the statistics literature and elsewhere. The techniques are illustrated with examples of real-world applications studies. Pointers are also provided to the diverse literature base where further details on applications, comparative studies and theoretical developments may be obtained"--Page [xv].

Discriminant Analysis and Applications
Discriminant Analysis and Applications

Author: T. Cacoullos

Publisher: Academic Press

Published: 2014-05-10

Total Pages: 455

ISBN-13: 1483268713

DOWNLOAD EBOOK

Discriminant Analysis and Applications comprises the proceedings of the NATO Advanced Study Institute on Discriminant Analysis and Applications held in Kifissia, Athens, Greece in June 1972. The book presents the theory and applications of Discriminant analysis, one of the most important areas of multivariate statistical analysis. This volume contains chapters that cover the historical development of discriminant analysis methods; logistic and quasi-linear discrimination; and distance functions. Medical and biological applications, and computer graphical analysis and graphical techniques for multidimensional data are likewise discussed. Statisticians, mathematicians, and biomathematicians will find the book very interesting.

Multivariate Statistical Analysis
Multivariate Statistical Analysis

Author: Parimal Mukhopadhyay

Publisher: World Scientific

Published: 2009

Total Pages: 568

ISBN-13: 9812791752

DOWNLOAD EBOOK

"This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner. It offers clear and concise development of the concepts; interpretation of the output of the analysis; and criteria for selection of the methods, taking into account the strengths and weaknesses of each." "This book is ideal as an advanced textbook for graduate students in statistics and other disciplines like social, biological and physical sciences. It will also be of benefit to professional statisticians." --Book Jacket.

A First Course in Multivariate Statistics
A First Course in Multivariate Statistics

Author: Bernard Flury

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 723

ISBN-13: 1475727658

DOWNLOAD EBOOK

A comprehensive and self-contained introduction to the field, carefully balancing mathematical theory and practical applications. It starts at an elementary level, developing concepts of multivariate distributions from first principles. After a chapter on the multivariate normal distribution reviewing the classical parametric theory, methods of estimation are explored using the plug-in principles as well as maximum likelihood. Two chapters on discrimination and classification, including logistic regression, form the core of the book, followed by methods of testing hypotheses developed from heuristic principles, likelihood ratio tests and permutation tests. Finally, the powerful self-consistency principle is used to introduce principal components as a method of approximation, rounded off by a chapter on finite mixture analysis.

Data Analysis, Classification and the Forward Search
Data Analysis, Classification and the Forward Search

Author: Sergio Zani

Publisher: Springer Science & Business Media

Published: 2007-08-06

Total Pages: 420

ISBN-13: 3540359788

DOWNLOAD EBOOK

This book presents new developments in data analysis, classification and multivariate statistics, and in their algorithmic implementation. The volume offers contributions to the theory of clustering and discrimination, multidimensional data analysis, data mining, and robust statistics with a special emphasis on the novel Forward Search approach. Many papers provide significant insight in a wide range of fields of application. Customer satisfaction and service evaluation are two examples of such emerging fields.

Discrimination and Privacy in the Information Society
Discrimination and Privacy in the Information Society

Author: Bart Custers

Publisher: Springer Science & Business Media

Published: 2012-08-11

Total Pages: 370

ISBN-13: 3642304877

DOWNLOAD EBOOK

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

Handbook of Statistical Analysis and Data Mining Applications
Handbook of Statistical Analysis and Data Mining Applications

Author: Ken Yale

Publisher: Elsevier

Published: 2017-11-09

Total Pages: 824

ISBN-13: 0124166458

DOWNLOAD EBOOK

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications