The Top Ten Algorithms In Data Mining

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The Top Ten Algorithms In Data Mining

Author : Xindong Wu
ISBN : 142008965X
Genre : Computers
File Size : 25.84 MB
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Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a particular algorithm and is written by either the original authors of the algorithm or world-class researchers who have extensively studied the respective algorithm. The book concentrates on the following important algorithms: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. Examples illustrate how each algorithm works and highlight its overall performance in a real-world application. The text covers key topics—including classification, clustering, statistical learning, association analysis, and link mining—in data mining research and development as well as in data mining, machine learning, and artificial intelligence courses. By naming the leading algorithms in this field, this book encourages the use of data mining techniques in a broader realm of real-world applications. It should inspire more data mining researchers to further explore the impact and novel research issues of these algorithms.
Category: Computers

Journeys To Data Mining

Author : Mohamed Medhat Gaber
ISBN : 9783642280474
Genre : Computers
File Size : 67.83 MB
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Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced core results for applications like business intelligence, spatio-temporal data analysis, bioinformatics, and stream data processing. The fifteen contributors to this volume are successful and well-known data mining scientists and professionals. Although by no means an exhaustive list, all of them have helped the field to gain the reputation and importance it enjoys today, through the many valuable contributions they have made. Mohamed Medhat Gaber has asked them (and many others) to write down their journeys through the data mining field, trying to answer the following questions: 1. What are your motives for conducting research in the data mining field? 2. Describe the milestones of your research in this field. 3. What are your notable success stories? 4. How did you learn from your failures? 5. Have you encountered unexpected results? 6. What are the current research issues and challenges in your area? 7. Describe your research tools and techniques. 8. How would you advise a young researcher to make an impact? 9. What do you predict for the next two years in your area? 10. What are your expectations in the long term? In order to maintain the informal character of their contributions, they were given complete freedom as to how to organize their answers. This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning. In addition, everyone else interested in the history of computer science may be surprised about the stunning successes and possible failures computer science careers (still) have to offer.
Category: Computers

Commercial Data Mining

Author : David Nettleton
ISBN : 9780124166585
Genre : Computers
File Size : 71.41 MB
Format : PDF
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Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book. Illustrates cost-benefit evaluation of potential projects Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools Approachable reference can be read from cover to cover by readers of all experience levels Includes practical examples and case studies as well as actionable business insights from author's own experience
Category: Computers

Data Mining

Author : Ian H. Witten
ISBN : 9780128043578
Genre : Computers
File Size : 39.26 MB
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Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at http://www.cs.waikato.ac.nz/ml/weka/book.html It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc. Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface Includes open-access online courses that introduce practical applications of the material in the book
Category: Computers

Data Mining And Statistics For Decision Making

Author : Stéphane Tufféry
ISBN : 0470979283
Genre : Computers
File Size : 64.83 MB
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Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. Starts from basic principles up to advanced concepts. Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. Gives practical tips for data mining implementation to solve real world problems. Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.
Category: Computers

Data Mining Practical Machine Learning Tools And Techniques

Author : Ian H. Witten
ISBN : 9780080890364
Genre : Computers
File Size : 25.31 MB
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Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
Category: Computers

Rough Granular Computing In Knowledge Discovery And Data Mining

Author : J. Stepaniuk
ISBN : 3540708006
Genre : Computers
File Size : 47.75 MB
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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.
Category: Computers

Advances In Knowledge Based And Intelligent Information And Engineering Systems

Author : Manuel Graña
ISBN : 9781614991045
Genre : Computers
File Size : 69.20 MB
Format : PDF
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In this 2012 edition of Advances in Knowledge-Based and Intelligent Information and Engineering Systems the latest innovations and advances in Intelligent Systems and related areas are presented by leading experts from all over the world. The 228 papers that are included cover a wide range of topics. One emphasis is on Information Processing, which has become a pervasive phenomenon in our civilization. While the majority of Information Processing is becoming intelligent in a very broad sense, major research in Semantics, Artificial Intelligence and Knowledge Engineering supports the domain specific applications that are becoming more and more present in our everyday living. Ontologies play a major role in the development of Knowledge Engineering in various domains, from Semantic Web down to the design of specific Decision Support Systems. Research on Ontologies and their applications is a highly active front of current Computational Intelligence science that is addressed here. Other subjects in this volume are modern Machine Learning, Lattice Computing and Mathematical Morphology.The wide scope and high quality of these contributions clearly show that knowledge engineering is a continuous living and evolving set of technologies aimed at improving the design and understanding of systems and their relations with humans.
Category: Computers

2002 Ieee International Conference On Data Mining

Author : Vipin Kumar
ISBN : 0769517544
Genre : Computers
File Size : 80.31 MB
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Consists of 72 full papers and 49 short papers from the December 2002 conference on the design, analysis, and implementation of data mining theory, systems, and applications. Topics of the full papers include evolutionary time series segmentation for stock data mining, cluster merging and splitting
Category: Computers

New Frontiers In Applied Data Mining

Author : Thanaruk Theeramunkong
ISBN : 9783642146398
Genre : Computers
File Size : 87.71 MB
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This book constitutes the proceedings of the PAKDD 2009 International Workshops on New Frontiers in Applied Data Mining, held in Bangkok, Thailand in April 2010.
Category: Computers

Introduction To Data Mining And Its Applications

Author : S. Sumathi
ISBN : 9783540343509
Genre : Computers
File Size : 48.73 MB
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This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.
Category: Computers

Top Ten Global Justice Law Review Articles 2007

Author : Amos N Guiora
ISBN : 0195376587
Genre : Law
File Size : 50.99 MB
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Top Ten Global Justice Law Review Articles 2007 is a thorough and accessible review of the most salient, the most controversial, and the most illuminating essays on security law in the previous calendar year. In this edition, Professor Amos Guiora presents the ten most vital and pertinent law review articles from 2007 written by both scholars who have already gained international prominence as experts in security law as well as emerging voices in the security-law debate. These articles deal with issues of terrorism, security law, and the preservation of civil liberties in the post-9/11 world. The chosen selections derive not just from the high quality and expertise of the articles' authors, but equally from the wide diversity of legal issues addressed by those authors. Guiora combines the expertise of scholars from such accredited institutions as Harvard, Stanford, the U.S Military Academy and the U.S. Department of Defense to provide a valuable resource for scholars and experts researching this important subject area. This annual review provides researchers with more than just an authoritative discussion on the most prominent security debates of the day; it also educates researchers on new issues that have received far too little attention in the press and in academia. These expert scholars and leaders tackle and give voice to these issues that range from cyberterror to detention of suspected terrorists to France's tightening of its civil liberties policy to new restrictions on religious philanthropy and beyond. Together, the vast knowledge and independent viewpoints represented by these ten authors make this volume, of what will be an annual review within the Terrorism, 2nd Series, a valuable resource for individuals new to the realm of security law and for advanced researchers with a sophisticated understanding of the field. Top Ten Global Justice Law Review Articles 2007 serves as a one-stop guidebook on how both the U.S. and the world generally are currently waging the war on terror.
Category: Law

2001 Ieee International Conference On Data Mining

Author : Nick Cercone
ISBN : 0769511198
Genre : Computers
File Size : 77.64 MB
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This proceedings of the November 2001 conference explores the design, analysis and implementation of data mining theory and systems. The 72 regular papers and 37 posters discuss data mining algorithms, data and knowledge representation, modeling of data to support data mining, scalability issues, st
Category: Computers

Programme Et R Sum S

Author : Geological Association of Canada. Meeting
ISBN : STANFORD:36105115031861
Genre : Geology
File Size : 74.36 MB
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Category: Geology

Abstract Volume

Author : Geological Association of Canada. Meeting
ISBN : UVA:X004651520
Genre : Geology
File Size : 25.34 MB
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Category: Geology

Data Mining Patterns

Author : Pascal Poncelet
ISBN : STANFORD:36105124045720
Genre : Computers
File Size : 23.72 MB
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"This book provides an overall view of recent solutions for mining, and explores new patterns,offering theoretical frameworks and presenting challenges and possible solutions concerning pattern extractions, emphasizing research techniques and real-world applications. It portrays research applications in data models, methodologies for mining patterns, multi-relational and multidimensional pattern mining, fuzzy data mining, data streaming and incremental mining"--Provided by publisher.
Category: Computers