Data Mining

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  • Author : Ian H. Witten
  • Publisher : Elsevier
  • Pages : 560 pages
  • ISBN : 9780080477022
  • Rating : 4/5 from 24 reviews
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Download or Read online Data Mining full in PDF, ePub and kindle. this book written by Ian H. Witten and published by Elsevier which was released on 13 July 2005 with total page 560 pages. We cannot guarantee that Data Mining book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; and much more. This text is designed for information systems practitioners, programmers, consultants, developers, information technology managers, specification writers as well as professors and students of graduate-level data mining and machine learning courses. Algorithmic methods at the heart of successful data mining—including tried and true techniques as well as leading edge methods Performance improvement techniques that work by transforming the input or output

Data Mining

Data Mining
  • Author : Ian H. Witten,Eibe Frank
  • Publisher : Elsevier
  • Release : 13 July 2005
GET THIS BOOK Data Mining

Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information

Data Mining and Data Visualization

Data Mining and Data Visualization
  • Author : Anonim
  • Publisher : Elsevier
  • Release : 02 May 2005
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Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering,

Data Mining Techniques

Data Mining Techniques
  • Author : Michael J. A. Berry,Gordon S. Linoff
  • Publisher : John Wiley & Sons
  • Release : 28 April 2004
GET THIS BOOK Data Mining Techniques

Packed with more than forty percent new and updated material,this edition shows business managers, marketing analysts, and datamining specialists how to harness fundamental data mining methodsand techniques to solve common types of business problems Each chapter covers a new data mining technique, and then showsreaders how to apply the technique for improved marketing, sales,and customer support The authors build on their reputation for concise, clear, andpractical explanations of complex concepts, making this book theperfect introduction to data mining

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
  • Author : David Cheung,Graham J. Williams,Qing Li
  • Publisher : Springer Science & Business Media
  • Release : 04 April 2001
GET THIS BOOK Advances in Knowledge Discovery and Data Mining

This book constitutes the refereed proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2001, held in Hong Kong, China in April 2001. The 38 revised full papers and 22 short papers presented were carefully reviewed and selected from a total of 152 submissions. The book offers topical sections on Web mining, text mining, applications and tools, concept hierarchies, feature selection, interestingness, sequence mining, spatial and temporal mining, association mining, classification and rule induction, clustering, and advanced topics and new methods.

Advanced Data Mining and Applications

Advanced Data Mining and Applications
  • Author : Xue Li,Shuliang Wang
  • Publisher : Springer Science & Business Media
  • Release : 12 July 2005
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This book constitutes the refereed proceedings of the First International Conference on Advanced Data Mining and Applications, ADMA 2005, held in Wuhan, China in July 2005. The conference was focused on sophisticated techniques and tools that can handle new fields of data mining, e.g. spatial data mining, biomedical data mining, and mining on high-speed and time-variant data streams; an expansion of data mining to new applications is also strived for. The 25 revised full papers and 75 revised short papers presented were carefully

Data Mining and Knowledge Discovery in Real Life Applications

Data Mining and Knowledge Discovery in Real Life Applications
  • Author : Julio Ponce,Adem Karahoca
  • Publisher : BoD – Books on Demand
  • Release : 01 January 2009
GET THIS BOOK Data Mining and Knowledge Discovery in Real Life Applications

This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.

Big Data Data Mining and Machine Learning

Big Data  Data Mining  and Machine Learning
  • Author : Jared Dean
  • Publisher : John Wiley & Sons
  • Release : 07 May 2014
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With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of

Predictive Analytics and Data Mining

Predictive Analytics and Data Mining
  • Author : Vijay Kotu,Bala Deshpande
  • Publisher : Morgan Kaufmann
  • Release : 27 November 2014
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Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores

Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences

Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences
  • Author : John J. McArdle,Gilbert Ritschard
  • Publisher : Routledge
  • Release : 15 August 2013
GET THIS BOOK Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences

This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different combinations of variables in large data sets. Methodological findings and conceptual models that explain reliable EDM techniques for predicting and understanding various risk mechanisms are integrated throughout. Numerous examples illustrate the use of these techniques in practice. Contributors provide insight through hands-on experiences with their own use of EDM

Mathematical Tools for Data Mining

Mathematical Tools for Data Mining
  • Author : Dan A. Simovici,Chaabane Djeraba
  • Publisher : Springer Science & Business Media
  • Release : 15 August 2008
GET THIS BOOK Mathematical Tools for Data Mining

This volume was born from the experience of the authors as researchers and educators,whichsuggeststhatmanystudentsofdataminingarehandicapped in their research by the lack of a formal, systematic education in its mat- matics. The data mining literature contains many excellent titles that address the needs of users with a variety of interests ranging from decision making to p- tern investigation in biological data. However, these books do not deal with the mathematical tools that are currently needed by data mining researchers and doctoral

Prediction of Highly Lucrative Companies Using Annual Statements A Data Mining Based Approach

Prediction of Highly Lucrative Companies Using Annual Statements  A Data Mining Based Approach
  • Author : Jurij Weinblat
  • Publisher : Anchor Academic Publishing (aap_verlag)
  • Release : 01 August 2014
GET THIS BOOK Prediction of Highly Lucrative Companies Using Annual Statements A Data Mining Based Approach

The intention of this study is to predict one year in advance whether a regarded firm will grow extraordinarily in the next year. This is crucial for private investors and fund managers who need to decide whether they should invest in a certain firm. Companies like Apple and Amazon have shown that people who recognized the potential of such companies at the right time earned a lot of money. The applied prediction models can also be used by politicians to

Data Mining VI

Data Mining VI
  • Author : A. Zanasi,C. A. Brebbia,Nelson F. F. Ebecken
  • Publisher : Wit Pr/Computational Mechanics
  • Release : 27 May 2022
GET THIS BOOK Data Mining VI

This book contains most of the papers presented at the Sixth International Conference on Data Mining held in Skiathos, Greece. Twenty-five countries from all the continents are represented in the papers published in the book, offering a real multinational and multicultural range of experiences and ideas.

Data Mining

Data Mining
  • Author : Robert Groth
  • Publisher : Prentice Hall
  • Release : 27 May 1998
GET THIS BOOK Data Mining

This book contains all the practical information, hands-on demos and software you need to understand data mining.This book doesn't just explain data mining concepts: it shows you exactly how to make the most of them. If you're in marketing, you'll learn how data mining can help you rank your customers by the likelihood they'll respond to your mailings. If you're in MIS, you'll learn exactly how to prepare relational data for data mining. You'll learn how to use each

Next Generation of Data Mining Applications

Next Generation of Data Mining Applications
  • Author : Mehmed Kantardzic,Jozef Zurada
  • Publisher : Wiley-IEEE Press
  • Release : 08 March 2005
GET THIS BOOK Next Generation of Data Mining Applications

Discover the next generation of data-mining tools and technology This book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting

Data Mining VII

Data Mining VII
  • Author : A. Zanasi,C. A. Brebbia,Nelson F. F. Ebecken
  • Publisher : Wit Pr/Computational Mechanics
  • Release : 27 May 2022
GET THIS BOOK Data Mining VII

This book publishes papers from the Seventh International Conference on Data Mining and Information Systems. The book brings together state-of-the-art research results and practical development experiences from researchers and application developers from many different areas. The book covers topics as diverse as: Data Mining Themes such as Text Mining; Web Content, Structure and Usage Mining; Clustering Technologies; Categorisation Methods; Link Analysis; Data Preparation; Applications in Business, Industry and Government; Customer Relationship Management; Competitive Intelligence; Applications in Science and Engineering; Mining