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Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications Author Robert Nisbet
ISBN-10 9780124166455
Release 2017-11-09
Pages 822
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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



Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications Author CTI Reviews
ISBN-10 9781467228398
Release 2016-09-26
Pages 100
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Facts101 is your complete guide to Handbook of Statistical Analysis and Data Mining Applications. In this book, you will learn topics such as PART III: Chapter 11 - Chapter 17, plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.



Practical Text Mining and Statistical Analysis for Non structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non structured Text Data Applications Author Gary Miner
ISBN-10 9780123870117
Release 2012-01-25
Pages 1000
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Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. Winner of a 2012 PROSE Award in Computing and Information Sciences from the Association of American Publishers, this book presents a comprehensive how-to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com Glossary of text mining terms provided in the appendix



Practical Predictive Analytics and Decisioning Systems for Medicine

Practical Predictive Analytics and Decisioning Systems for Medicine Author Linda Miner
ISBN-10 9780124116405
Release 2014-09-27
Pages 1110
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With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost–efficient manner. Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions. Includes models and applications of predictive analytics why they are important and how they can be used in healthcare and medical research Provides real world step-by-step tutorials to help beginners understand how the predictive analytic processes works and to successfully do the computations Demonstrates methods to help sort through data to make better observations and allow you to make better predictions



Data Mining

Data Mining Author Mehmed Kantardzic
ISBN-10 9781118029138
Release 2011-08-04
Pages 520
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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]



Handbook of Educational Data Mining

Handbook of Educational Data Mining Author Cristobal Romero
ISBN-10 1439804583
Release 2010-10-25
Pages 535
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Handbook of Educational Data Mining (EDM) provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed. Researchers at the Forefront of the Field Discuss Essential Topics and the Latest Advances With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It brings the educational and data mining communities together, helping education experts understand what types of questions EDM can address and helping data miners understand what types of questions are important to educational design and educational decision making. Encouraging readers to integrate EDM into their research and practice, this timely handbook offers a broad, accessible treatment of essential EDM techniques and applications. It provides an excellent first step for newcomers to the EDM community and for active researchers to keep abreast of recent developments in the field.



Ethical Data Mining Applications for Socio Economic Development

Ethical Data Mining Applications for Socio Economic Development Author Hakikur Rahman
ISBN-10 9781466640795
Release 2013-05-31
Pages 349
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"This book provides an overview of data mining techniques under an ethical lens, investigating developments in research best practices and examining experimental cases to identify potential ethical dilemmas in the information and communications technology sector"--Provided by publisher.



Data Mining Algorithms

Data Mining Algorithms Author Pawel Cichosz
ISBN-10 9781118950807
Release 2014-11-17
Pages 720
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Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.



Data Mining and Data Visualization

Data Mining and Data Visualization Author
ISBN-10 0080459404
Release 2005-05-02
Pages 800
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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, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. Distinguished contributors who are international experts in aspects of data mining Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions Thorough discussion of data visualization issues blending statistical, human factors, and computational insights



Data Mining Practical Machine Learning Tools and Techniques

Data Mining  Practical Machine Learning Tools and Techniques Author Ian H. Witten
ISBN-10 9780080890364
Release 2011-02-03
Pages 664
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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



The Oxford Handbook of Corpus Phonology

The Oxford Handbook of Corpus Phonology Author Jacques Durand
ISBN-10 9780191669279
Release 2014-06-05
Pages 704
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This handbook presents the first systematic account of corpus phonology - the employment of corpora for studying speakers' and listeners' acquisition and knowledge of the sound system of their native languages and the principles underlying those systems. The first part of the book discusses the design, compilation, and use of phonological corpora, while the second looks at specific applications. Part 3 presents the tools and methods used, while the final part examines a number of currently available phonological corpora in various languages. It will appeal not only to those working with phonological corpora, but also to researchers and students of phonology and phonetics more generally, as well as to all those interested in language variation, dialectology, language acquisition, and sociolinguistics.



Business Analytics Principles Concepts and Applications with SAS

Business Analytics Principles  Concepts  and Applications with SAS Author Marc J. Schniederjans
ISBN-10 9780133989571
Release 2014-09-12
Pages 352
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Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications with SAS brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. Business Analytics Principles, Concepts, and Applications with SAS will be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.



Data Mining and Knowledge Discovery Handbook

Data Mining and Knowledge Discovery Handbook Author Oded Maimon
ISBN-10 9780387254654
Release 2006-05-28
Pages 1383
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Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.



Odysseas

Odysseas Author James Joyce
ISBN-10 OCLC:31136650
Release 1971
Pages 1190
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Odysseas has been writing in one form or another for most of life. You can find so many inspiration from Odysseas also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Odysseas book for free.



The Oxford Handbook of Quantitative Methods in Psychology Vol 2

The Oxford Handbook of Quantitative Methods in Psychology  Vol  2 Author Todd D. Little
ISBN-10 9780199934898
Release 2013-03-21
Pages 736
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The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for learning and reviewing current best-practices in a quantitative methods across the social, behavioral, and educational sciences.



Handbook Of Business Practices And Growth In Emerging Markets

Handbook Of Business Practices And Growth In Emerging Markets Author Singh Satyendra
ISBN-10 9789814471817
Release 2009-10-22
Pages 576
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The Handbook of Business Practices and Growth in Emerging Markets consists of a collection of specially commissioned chapters that describe the current business environment, organizational culture, consumer behavior, financial investment climate, and examples of best prevailing practices in emerging markets. It covers all the major functional areas of business — marketing, strategy, operations and finance — in all continents. The focus of each chapter is on the identification of different business issues in different emerging markets (including Asia, Africa and South America) and on the implementation of a proposed set of recommendations, using both qualitative and quantitative techniques to assist in decision-making and in improving organizational efficiency and effectiveness. Readers will also appreciate the multidimensional view of financial and non-financial performance measurement of businesses.Specifically, the goal of this research-based handbook is to provide a comprehensive guide for business students and managers by discussing a range of issues from the diverse emerging markets and enabling them to develop a strategic mindset for a market-oriented culture. Given the changing business dynamics, government policies and demands in industries, this handbook is both timely and topical.



Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence Author Trivedi, Shrawan Kumar
ISBN-10 9781522520320
Release 2017-02-14
Pages 438
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The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.