Outlier Analysis

Author: Charu C. Aggarwal

Publisher: Springer

ISBN: 3319475789

Category: Computers

Page: 466

View: 8705

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This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods. Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data. Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner. The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.

Überflieger

Warum manche Menschen erfolgreich sind - und andere nicht

Author: Malcolm Gladwell

Publisher: Campus Verlag

ISBN: 3593405016

Category: Political Science

Page: 272

View: 3208

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Malcolm Gladwell, Bestsellerautor und Star des amerikanischen Buchmarkts, hat die wahren Ursachen des Erfolgs untersucht und darüber ein lehrreiches, faszinierendes Buch geschrieben. Es steckt voller Geschichten und Beispiele, die zeigen, dass auch außergewöhnlicher Erfolg selten etwas mit individuellen Eigenschaften zu tun hat, sondern mit Gegebenheiten, die es dem einen leicht und dem anderen unmöglich machen, erfolgreich zu sein. Die Frage ist nicht, wie jemand ist, sondern woher er kommt: Welche Bedingungen haben diesen Menschen hervorgebracht? Auf seiner anregenden intellektuellen Erkundung der Welt der Überflieger erklärt Gladwell unter anderem das Geheimnis der Softwaremilliardäre, wie man ein herausragender Fußballer wird, warum Asiaten so gut in Mathe sind und was die Beatles zur größten Band aller Zeiten machte.

Überflieger

Warum manche Menschen erfolgreich sind - und andere nicht

Author: Malcolm Gladwell

Publisher: Campus Verlag

ISBN: 3593388383

Category: Political Science

Page: 272

View: 8052

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Malcolm Gladwell, Bestsellerautor und Star des amerikanischen Buchmarkts, hat die wahren Ursachen des Erfolgs untersucht und darüber ein lehrreiches, faszinierendes Buch geschrieben. Es steckt voller Geschichten und Beispiele, die zeigen, dass auch außergewöhnlicher Erfolg selten etwas mit individuellen Eigenschaften zu tun hat, sondern mit Gegebenheiten, die es dem einen leicht und dem anderen unmöglich machen, erfolgreich zu sein. Die Frage ist nicht, wie jemand ist, sondern woher er kommt: Welche Bedingungen haben diesen Menschen hervorgebracht? Auf seiner anregenden intellektuellen Erkundung der Welt der Überflieger erklärt Gladwell unter anderem das Geheimnis der Softwaremilliardäre, wie man ein herausragender Fußballer wird, warum Asiaten so gut in Mathe sind und was die Beatles zur größten Band aller Zeiten machte.

Überflieger

warum manche Menschen erfolgreich sind - und andere nicht

Author: Malcolm Gladwell,Jürgen Neubauer

Publisher: N.A

ISBN: 9783492258197

Category:

Page: 272

View: 738

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Robust Regression and Outlier Detection

Author: Peter J. Rousseeuw,Annick M. Leroy

Publisher: John Wiley & Sons

ISBN: 0471725374

Category: Mathematics

Page: 329

View: 616

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WILEY-INTERSCIENCE PAPERBACK SERIES 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. "The writing style is clear and informal, and much of the discussion is oriented to application. In short, the book is a keeper." –Mathematical Geology "I would highly recommend the addition of this book to the libraries of both students and professionals. It is a useful textbook for the graduate student, because it emphasizes both the philosophy and practice of robustness in regression settings, and it provides excellent examples of precise, logical proofs of theorems. . . .Even for those who are familiar with robustness, the book will be a good reference because it consolidates the research in high-breakdown affine equivariant estimators and includes an extensive bibliography in robust regression, outlier diagnostics, and related methods. The aim of this book, the authors tell us, is ‘to make robust regression available for everyday statistical practice.’ Rousseeuw and Leroy have included all of the necessary ingredients to make this happen." –Journal of the American Statistical Association

Outlier Detection for Temporal Data

Author: Manish Gupta,Jing Gao,Charu Aggarwal,Jiawei Han

Publisher: Morgan & Claypool Publishers

ISBN: 162705376X

Category: Computers

Page: 129

View: 9606

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Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book. A large number of applications generate temporal datasets. For example, in our everyday life, various kinds of records like credit, personnel, financial, judicial, medical, etc., are all temporal. This stresses the need for an organized and detailed study of outliers with respect to such temporal data. In the past decade, there has been a lot of research on various forms of temporal data including consecutive data snapshots, series of data snapshots and data streams. Besides the initial work on time series, researchers have focused on rich forms of data including multiple data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for temporal outlier detection are very different. In this book, we will present an organized picture of both recent and past research in temporal outlier detection. We start with the basics and then ramp up the reader to the main ideas in state-of-the-art outlier detection techniques. We motivate the importance of temporal outlier detection and brief the challenges beyond usual outlier detection. Then, we list down a taxonomy of proposed techniques for temporal outlier detection. Such techniques broadly include statistical techniques (like AR models, Markov models, histograms, neural networks), distance- and density-based approaches, grouping-based approaches (clustering, community detection), network-based approaches, and spatio-temporal outlier detection approaches. We summarize by presenting a wide collection of applications where temporal outlier detection techniques have been applied to discover interesting outliers.

Outlier Ensembles

An Introduction

Author: Charu C. Aggarwal,Saket Sathe

Publisher: Springer

ISBN: 3319547658

Category: Computers

Page: 276

View: 5318

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This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. In addition, it covers the techniques with which such methods can be made more effective. A formal classification of these methods is provided, and the circumstances in which they work well are examined. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification. The similarities and (subtle) differences in the ensemble techniques for the classification and outlier detection problems are explored. These subtle differences do impact the design of ensemble algorithms for the latter problem. This book can be used for courses in data mining and related curricula. Many illustrative examples and exercises are provided in order to facilitate classroom teaching. A familiarity is assumed to the outlier detection problem and also to generic problem of ensemble analysis in classification. This is because many of the ensemble methods discussed in this book are adaptations from their counterparts in the classification domain. Some techniques explained in this book, such as wagging, randomized feature weighting, and geometric subsampling, provide new insights that are not available elsewhere. Also included is an analysis of the performance of various types of base detectors and their relative effectiveness. The book is valuable for researchers and practitioners for leveraging ensemble methods into optimal algorithmic design.

Hybrid Artificial Intelligent Systems

12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings

Author: Francisco Javier Martínez de Pisón,Rubén Urraca,Héctor Quintián,Emilio Corchado

Publisher: Springer

ISBN: 3319596500

Category: Computers

Page: 725

View: 2578

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This volume constitutes the refereed proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, held in La Rioja, Spain, in June 2017. The 60 full papers published in this volume were carefully reviewed and selected from 130 submissions. They are organized in the following topical sections: data mining, knowledge discovery and big data; bioinspired models and evolutionary computing; learning algorithms; visual analysis and advanced data processing techniques; data mining applications; and hybrid intelligent applications.

Die Kunst des Vertrauens

Author: Bruce Schneier

Publisher: MITP-Verlags GmbH & Co. KG

ISBN: 3826692160

Category:

Page: 464

View: 5597

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In dieser brillanten Abhandlung, die mit philosophischen, vor allem spieltheoretischen Überlegungen ebenso zu überzeugen weiß wie mit fundierten wissenschaftlichen Erkenntnissen aus der Soziologie, Biologie und Anthroplogie, geht der IT-Sicherheitsexperte Bruce Schneier der Frage nach: Wieviel Vertrauen (der Individuen untereinander) braucht eine lebendige, fortschrittsorientierte Gesellschaft und wieviel Vertrauensbruch darf bzw. muss sie sich leisten?

Advances in Knowledge Discovery and Data Mining

10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, Proceedings

Author: Wee Keong Ng

Publisher: Springer Science & Business Media

ISBN: 3540332065

Category: Computers

Page: 879

View: 1768

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The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference in the area of data mining and knowledge discovery. This year marks the tenth anniversary of the successful annual series of PAKDD conferences held in the Asia Pacific region. It was with pleasure that we hosted PAKDD 2006 in Singapore again, since the inaugural PAKDD conference was held in Singapore in 1997. PAKDD 2006 continues its tradition of providing an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all aspects of KDD data mining, including data cleaning, data warehousing, data mining techniques, knowledge visualization, and data mining applications. This year, we received 501 paper submissions from 38 countries and regions in Asia, Australasia, North America and Europe, of which we accepted 67 (13.4%) papers as regular papers and 33 (6.6%) papers as short papers. The distribution of the accepted papers was as follows: USA (17%), China (16%), Taiwan (10%), Australia (10%), Japan (7%), Korea (7%), Germany (6%), Canada (5%), Hong Kong (3%), Singapore (3%), New Zealand (3%), France (3%), UK (2%), and the rest from various countries in the Asia Pacific region.

Empirical Direction in Design and Analysis

Author: Norman H. Anderson

Publisher: Psychology Press

ISBN: 1135643385

Category: Psychology

Page: 880

View: 4391

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The goal of Norman H. Anderson's new book is to help students develop skills of scientific inference. To accomplish this he organized the book around the "Experimental Pyramid"--six levels that represent a hierarchy of considerations in empirical investigation--conceptual framework, phenomena, behavior, measurement, design, and statistical inference. To facilitate conceptual and empirical understanding, Anderson de-emphasizes computational formulas and null hypothesis testing. Other features include: *emphasis on visual inspection as a basic skill in experimental analysis to help students develop an intuitive appreciation of data patterns; *exercises that emphasize development of conceptual and empirical application of methods of design and analysis and de-emphasize formulas and calculations; and *heavier emphasis on confidence intervals than significance tests. The book is intended for use in graduate-level experimental design/research methods or statistics courses in psychology, education, and other applied social sciences, as well as a professional resource for active researchers. The first 12 chapters present the core concepts graduate students must understand. The next nine chapters serve as a reference handbook by focusing on specialized topics with a minimum of technicalities.

Identification of Outliers

Author: D. Hawkins

Publisher: Springer Science & Business Media

ISBN: 9401539944

Category: Science

Page: 188

View: 3793

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The problem of outliers is one of the oldest in statistics, and during the last century and a half interest in it has waxed and waned several times. Currently it is once again an active research area after some years of relative neglect, and recent work has solved a number of old problems in outlier theory, and identified new ones. The major results are, however, scattered amongst many journal articles, and for some time there has been a clear need to bring them together in one place. That was the original intention of this monograph: but during execution it became clear that the existing theory of outliers was deficient in several areas, and so the monograph also contains a number of new results and conjectures. In view of the enormous volume ofliterature on the outlier problem and its cousins, no attempt has been made to make the coverage exhaustive. The material is concerned almost entirely with the use of outlier tests that are known (or may reasonably be expected) to be optimal in some way. Such topics as robust estimation are largely ignored, being covered more adequately in other sources. The numerous ad hoc statistics proposed in the early work on the grounds of intuitive appeal or computational simplicity also are not discussed in any detail.

Data Mining: Concepts and Techniques

Author: Jiawei Han,Jian Pei,Micheline Kamber

Publisher: Elsevier

ISBN: 9780123814807

Category: Computers

Page: 744

View: 2128

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Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Conducting Meta-Analysis Using SAS

Author: Winfred Arthur, Jr.,Winston Bennett,Allen I. Huffcutt

Publisher: Psychology Press

ISBN: 1135643466

Category: Psychology

Page: 208

View: 8042

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Conducting Meta-Analysis Using SAS reviews the meta-analysis statistical procedure and shows the reader how to conduct one using SAS. It presents and illustrates the use of the PROC MEANS procedure in SAS to perform the data computations called for by the two most commonly used meta-analytic procedures, the Hunter & Schmidt and Glassian approaches. This book serves as both an operational guide and user's manual by describing and explaining the meta-analysis procedures and then presenting the appropriate SAS program code for computing the pertinent statistics. The practical, step-by-step instructions quickly prepare the reader to conduct a meta-analysis. Sample programs available on the Web further aid the reader in understanding the material. Intended for researchers, students, instructors, and practitioners interested in conducting a meta-analysis, the presentation of both formulas and their associated SAS program code keeps the reader and user in touch with technical aspects of the meta-analysis process. The book is also appropriate for advanced courses in meta-analysis psychology, education, management, and other applied social and health sciences departments.

Data Mining and Knowledge Discovery Handbook

Author: Oded Z. Maimon,Lior Rokach

Publisher: Springer Science & Business Media

ISBN: 9780387244358

Category: Computers

Page: 1383

View: 8644

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Organizes major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD). This book provides algorithmic descriptions of classic methods, and also suitable for professionals in fields such as computing applications, information systems management, and more.

Evolutionary Statistical Procedures

An Evolutionary Computation Approach to Statistical Procedures Designs and Applications

Author: Roberto Baragona,Francesco Battaglia,Irene Poli

Publisher: Springer Science & Business Media

ISBN: 9783642162183

Category: Computers

Page: 276

View: 7491

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This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions are infeasible. Evolutionary algorithms represent a powerful and easily understood means of approximating the optimum value in a variety of settings. The proposed text seeks to guide readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods (including both stand-alone evolutionary algorithms and hybrid crosses of these procedures with standard statistical algorithms like Metropolis-Hastings) in a variety of applications. This book would serve as an excellent reference work for statistical researchers at an advanced graduate level or beyond, particularly those with a strong background in computer science.

Modern Analysis of Customer Surveys

with Applications using R

Author: Ron S. Kenett,Silvia Salini

Publisher: John Wiley & Sons

ISBN: 1119961386

Category: Business & Economics

Page: 352

View: 691

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Customer survey studies deals with customers, consumers and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. As demonstrated in this book, integrating such basic analysis with more advanced tools, provides insights on non-obvious patterns and important relationships between the survey variables. This knowledge can significantly affect the conclusions derived from a survey. Key features: Provides an integrated, case-studies based approach to analysing customer survey data. Presents a general introduction to customer surveys, within an organization’s business cycle. Contains classical techniques with modern and non standard tools. Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments. Accompanied by a supporting website containing datasets and R scripts. Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields.