Data Mining Methods And Models Set
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Data Mining Methods Models
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Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2006-06
Data Mining Methods Models written by Daniel T. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06 with Data mining categories.
The book introduces readers to data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis. Taking a unified approach based on CRISP methodology, the book discusses the latest techniques for uncovering hidden nuggets of information and provides insight into how the data mining algorithms actually work with hands-on experience performing data mining on large data sets. · Dimension Reduction Methods · Regression Modeling · Multiple Regression and Model Building · Logistic Regression · Naïve Bayes and Bayesian Networks · Genetic Algorithms · Case Study: Modeling Response to Direct-Mail Marketing
Data Mining Methods And Models
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Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2006-02-02
Data Mining Methods And Models written by Daniel T. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-02 with Computers categories.
Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information * The insight into how the data mining algorithms actually work * The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a "white box" methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, "Modeling Response to Direct-Mail Marketing" * Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises * Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software * Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.
Data Mining And Predictive Analytics
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Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-16
Data Mining And Predictive Analytics written by Daniel T. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-16 with Computers categories.
Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Data Mining
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Author : Mehmed Kantardzic
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-23
Data Mining written by Mehmed Kantardzic and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-23 with Computers categories.
Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on the topic—explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.
Data Mining
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Author : Mehmed Kantardzic
language : en
Publisher: John Wiley & Sons
Release Date : 2011-08-16
Data Mining written by Mehmed Kantardzic and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-16 with Computers categories.
This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades. If you are an instructor or professor and would like to obtain instructor’s materials, please visit http://booksupport.wiley.com If you are an instructor or professor and would like to obtain a solutions manual, please send an email to: [email protected]
Data Mining Methods And Models Set
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Author : Daniel T. Larose
language : en
Publisher: Wiley-Interscience
Release Date : 2007-06-29
Data Mining Methods And Models Set written by Daniel T. Larose and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-29 with Computers categories.
Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information* The insight into how the data mining algorithms actually work* The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a white box methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, Modeling Response to Direct-Mail Marketing* Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises* Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software* Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.
Advanced Data Mining Techniques
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Author : David L. Olson
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-01
Advanced Data Mining Techniques written by David L. Olson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-01 with Business & Economics categories.
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.
Business Modeling And Data Mining
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Author : Dorian Pyle
language : en
Publisher: Elsevier
Release Date : 2003-05-17
Business Modeling And Data Mining written by Dorian Pyle and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-17 with Computers categories.
Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem. This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations. · Teaches how to discover, construct and refine models that are useful in business situations· Teaches how to design, discover and develop the data necessary for mining · Provides a practical approach to mining data for all business situations· Provides a comprehensive, easy-to-use, fully interactive methodology for building models and mining data· Provides pointers to supplemental online resources, including a downloadable version of the methodology and software tools.
Handbook Of Statistical Analysis And Data Mining Applications
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Author : Ken Yale
language : en
Publisher: Elsevier
Release Date : 2017-11-09
Handbook Of Statistical Analysis And Data Mining Applications written by Ken Yale and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-09 with Mathematics categories.
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
Data Mining Methods For The Content Analyst
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Author : Kalev Leetaru
language : en
Publisher: Routledge
Release Date : 2012
Data Mining Methods For The Content Analyst written by Kalev Leetaru and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
This research reference introduces readers to the data mining technologies available for use in content analysis research. Supporting the increasingly popular trend of employing digital analysis methodologies in the humanities, arts, and social sciences, this work provides crucial answers for researchers who are not familiar with data mining approaches and who do not know what they can do, how they work, or how their strengths and weaknesses match up to the strengths and weaknesses of human coded content analysis data. Offering valuable insights and guidance for using automated analytical techniques in content analysis research, this guide will appeal to both novice and experienced researchers throughout the humanities, arts, and social sciences.