Foundations Of Data Mining And Knowledge Discovery

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Foundations of Data Mining and Knowledge Discovery

Tsau Young Lin,Setsuo Ohsuga,Churn-Jung Liau,Xiaohua Hu,Shusaku Tsumoto
Foundations of Data Mining and Knowledge Discovery Book PDF

Author : Tsau Young Lin,Setsuo Ohsuga,Churn-Jung Liau,Xiaohua Hu,Shusaku Tsumoto
Publisher : Springer Science & Business Media
Page : 400 pages
File Size : 53,6 Mb
Release : 2005-09-02
Category : Computers
ISBN : 3540262571

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Foundations of Data Mining and Knowledge Discovery by Tsau Young Lin,Setsuo Ohsuga,Churn-Jung Liau,Xiaohua Hu,Shusaku Tsumoto Pdf

"Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.

Statistical Data Analytics

Walter W. Piegorsch
Statistical Data Analytics Book PDF

Author : Walter W. Piegorsch
Publisher : John Wiley & Sons
Page : 227 pages
File Size : 45,8 Mb
Release : 2015-12-21
Category : Mathematics
ISBN : 9781119030652

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Statistical Data Analytics by Walter W. Piegorsch Pdf

Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.

Scientific Data Mining and Knowledge Discovery

Mohamed Medhat Gaber
Scientific Data Mining and Knowledge Discovery Book PDF

Author : Mohamed Medhat Gaber
Publisher : Springer Science & Business Media
Page : 398 pages
File Size : 45,9 Mb
Release : 2009-09-19
Category : Computers
ISBN : 9783642027888

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Scientific Data Mining and Knowledge Discovery by Mohamed Medhat Gaber Pdf

Mohamed Medhat Gaber “It is not my aim to surprise or shock you – but the simplest way I can summarise is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which the human mind has been applied” by Herbert A. Simon (1916-2001) 1Overview This book suits both graduate students and researchers with a focus on discovering knowledge from scienti c data. The use of computational power for data analysis and knowledge discovery in scienti c disciplines has found its roots with the re- lution of high-performance computing systems. Computational science in physics, chemistry, and biology represents the rst step towards automation of data analysis tasks. The rational behind the developmentof computationalscience in different - eas was automating mathematical operations performed in those areas. There was no attention paid to the scienti c discovery process. Automated Scienti c Disc- ery (ASD) [1–3] represents the second natural step. ASD attempted to automate the process of theory discovery supported by studies in philosophy of science and cognitive sciences. Although early research articles have shown great successes, the area has not evolved due to many reasons. The most important reason was the lack of interaction between scientists and the automating systems.

Statistical Data Analytics

Walter W. Piegorsch
Statistical Data Analytics Book PDF

Author : Walter W. Piegorsch
Publisher : John Wiley & Sons
Page : 232 pages
File Size : 55,6 Mb
Release : 2016-03-22
Category : Mathematics
ISBN : 9781119043645

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Statistical Data Analytics by Walter W. Piegorsch Pdf

Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.

Data Mining: Foundations and Practice

Tsau Young Lin,Ying Xie,Anita Wasilewska,Churn-Jung Liau
Data Mining Foundations and Practice Book PDF

Author : Tsau Young Lin,Ying Xie,Anita Wasilewska,Churn-Jung Liau
Publisher : Springer
Page : 562 pages
File Size : 41,5 Mb
Release : 2008-08-17
Category : Technology & Engineering
ISBN : 9783540784883

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Data Mining: Foundations and Practice by Tsau Young Lin,Ying Xie,Anita Wasilewska,Churn-Jung Liau Pdf

The IEEE ICDM 2004 workshop on the Foundation of Data Mining and the IEEE ICDM 2005 workshop on the Foundation of Semantic Oriented Data and Web Mining focused on topics ranging from the foundations of data mining to new data mining paradigms. The workshops brought together both data mining researchers and practitioners to discuss these two topics while seeking solutions to long standing data mining problems and stimul- ing new data mining research directions. We feel that the papers presented at these workshops may encourage the study of data mining as a scienti?c ?eld and spark new communications and collaborations between researchers and practitioners. Toexpressthevisionsforgedintheworkshopstoawiderangeofdatam- ing researchers and practitioners and foster active participation in the study of foundations of data mining, we edited this volume by involving extended and updated versions of selected papers presented at those workshops as well as some other relevant contributions. The content of this book includes st- ies of foundations of data mining from theoretical, practical, algorithmical, and managerial perspectives. The following is a brief summary of the papers contained in this book.

Foundations and Advances in Data Mining

Wesley Chu,Tsau Young Lin
Foundations and Advances in Data Mining Book PDF

Author : Wesley Chu,Tsau Young Lin
Publisher : Springer Science & Business Media
Page : 360 pages
File Size : 50,6 Mb
Release : 2005-09-15
Category : Computers
ISBN : 3540250573

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Foundations and Advances in Data Mining by Wesley Chu,Tsau Young Lin Pdf

With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.

Data Mining and Machine Learning

Mohammed J. Zaki,Wagner Meira, Jr
Data Mining and Machine Learning Book PDF

Author : Mohammed J. Zaki,Wagner Meira, Jr
Publisher : Cambridge University Press
Page : 779 pages
File Size : 50,6 Mb
Release : 2020-01-30
Category : Business & Economics
ISBN : 9781108473989

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Data Mining and Machine Learning by Mohammed J. Zaki,Wagner Meira, Jr Pdf

New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

Data Mining Methods for Knowledge Discovery

Krzysztof J. Cios,Witold Pedrycz,Roman W. Swiniarski
Data Mining Methods for Knowledge Discovery Book PDF

Author : Krzysztof J. Cios,Witold Pedrycz,Roman W. Swiniarski
Publisher : Springer
Page : 495 pages
File Size : 52,9 Mb
Release : 1998-08-31
Category : Computers
ISBN : 0792382528

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Data Mining Methods for Knowledge Discovery by Krzysztof J. Cios,Witold Pedrycz,Roman W. Swiniarski Pdf

Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.

Foundations of Predictive Analytics

James Wu,Stephen Coggeshall
Foundations of Predictive Analytics Book PDF

Author : James Wu,Stephen Coggeshall
Publisher : CRC Press
Page : 338 pages
File Size : 44,8 Mb
Release : 2012-02-15
Category : Business & Economics
ISBN : 9781439869482

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Foundations of Predictive Analytics by James Wu,Stephen Coggeshall Pdf

Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety

Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques

Evangelos Triantaphyllou,Giovanni Felici
Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques Book PDF

Author : Evangelos Triantaphyllou,Giovanni Felici
Publisher : Springer Science & Business Media
Page : 784 pages
File Size : 51,8 Mb
Release : 2006-09-10
Category : Computers
ISBN : 9780387342962

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Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques by Evangelos Triantaphyllou,Giovanni Felici Pdf

This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.

Knowledge Discovery and Data Mining

O. Maimon,M. Last
Knowledge Discovery and Data Mining Book PDF

Author : O. Maimon,M. Last
Publisher : Springer Science & Business Media
Page : 192 pages
File Size : 49,5 Mb
Release : 2000-12-31
Category : Computers
ISBN : 0792366476

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Knowledge Discovery and Data Mining by O. Maimon,M. Last Pdf

This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).

Next Generation of Data Mining

Hillol Kargupta,Jiawei Han,Philip S. Yu,Rajeev Motwani,Vipin Kumar
Next Generation of Data Mining Book PDF

Author : Hillol Kargupta,Jiawei Han,Philip S. Yu,Rajeev Motwani,Vipin Kumar
Publisher : CRC Press
Page : 640 pages
File Size : 50,5 Mb
Release : 2008-12-24
Category : Computers
ISBN : 9781420085877

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Next Generation of Data Mining by Hillol Kargupta,Jiawei Han,Philip S. Yu,Rajeev Motwani,Vipin Kumar Pdf

Drawn from the US National Science Foundation's Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field.Gathering perspectives from top experts across different di

Foundations and Novel Approaches in Data Mining

Tsau Young Lin,Setsuo Ohsuga,Churn-Jung Liau,Xiaohua Hu
Foundations and Novel Approaches in Data Mining Book PDF

Author : Tsau Young Lin,Setsuo Ohsuga,Churn-Jung Liau,Xiaohua Hu
Publisher : Springer Science & Business Media
Page : 398 pages
File Size : 40,6 Mb
Release : 2005-11-03
Category : Mathematics
ISBN : 3540283153

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Foundations and Novel Approaches in Data Mining by Tsau Young Lin,Setsuo Ohsuga,Churn-Jung Liau,Xiaohua Hu Pdf

Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. Currently, application oriented engineers are only concerned with their immediate problems, which results in an ad hoc method of problem solving. Researchers, on the other hand, lack an understanding of the practical issues of data-mining for real-world problems and often concentrate on issues that are of no significance to the practitioners. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research. A set of well respected data mining theoreticians were invited to present their views on the fundamental science of data mining. We have also called on researchers with practical data mining experiences to present new important data-mining topics.

Knowledge Discovery and Measures of Interest

Robert J. Hilderman,Howard J. Hamilton
Knowledge Discovery and Measures of Interest Book PDF

Author : Robert J. Hilderman,Howard J. Hamilton
Publisher : Springer Science & Business Media
Page : 170 pages
File Size : 46,7 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9781475732832

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Knowledge Discovery and Measures of Interest by Robert J. Hilderman,Howard J. Hamilton Pdf

Knowledge Discovery and Measures of Interest is a reference book for knowledge discovery researchers, practitioners, and students. The knowledge discovery researcher will find that the material provides a theoretical foundation for measures of interest in data mining applications where diversity measures are used to rank summaries generated from databases. The knowledge discovery practitioner will find solid empirical evidence on which to base decisions regarding the choice of measures in data mining applications. The knowledge discovery student in a senior undergraduate or graduate course in databases and data mining will find the book is a good introduction to the concepts and techniques of measures of interest. In Knowledge Discovery and Measures of Interest, we study two closely related steps in any knowledge discovery system: the generation of discovered knowledge; and the interpretation and evaluation of discovered knowledge. In the generation step, we study data summarization, where a single dataset can be generalized in many different ways and to many different levels of granularity according to domain generalization graphs. In the interpretation and evaluation step, we study diversity measures as heuristics for ranking the interestingness of the summaries generated. The objective of this work is to introduce and evaluate a technique for ranking the interestingness of discovered patterns in data. It consists of four primary goals: To introduce domain generalization graphs for describing and guiding the generation of summaries from databases. To introduce and evaluate serial and parallel algorithms that traverse the domain generalization space described by the domain generalization graphs. To introduce and evaluate diversity measures as heuristic measures of interestingness for ranking summaries generated from databases. To develop the preliminary foundation for a theory of interestingness within the context of ranking summaries generated from databases. Knowledge Discovery and Measures of Interest is suitable as a secondary text in a graduate level course and as a reference for researchers and practitioners in industry.

Rough – Granular Computing in Knowledge Discovery and Data Mining

J. Stepaniuk
Rough Granular Computing in Knowledge Discovery and Data Mining Book PDF

Author : J. Stepaniuk
Publisher : Springer Science & Business Media
Page : 162 pages
File Size : 40,7 Mb
Release : 2008-08-19
Category : Computers
ISBN : 9783540708001

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Rough – Granular Computing in Knowledge Discovery and Data Mining by J. Stepaniuk Pdf

This book covers methods based on a combination of granular computing, rough sets, and knowledge discovery in data mining (KDD). The discussion of KDD foundations based on the rough set approach and granular computing feature illustrative applications.