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Applied Data Mining For Forecasting Using Sas
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Book Synopsis Applied Data Mining for Forecasting Using SAS by : Tim Rey
Download or read book Applied Data Mining for Forecasting Using SAS written by Tim Rey and published by SAS Institute. This book was released on 2012-07-02 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select useful candidate input variables for time series regression models in environments when the number of candidates is large, and identifies the correlation structure between selected candidate inputs and the forecast variable. This book is essential for forecasting practitioners who need to understand the practical issues involved in applied forecasting in a business setting. Through numerous real-world examples, the authors demonstrate how to effectively use SAS software to meet their industrial forecasting needs. This book is part of the SAS Press program.
Book Synopsis SAS for Forecasting Time Series, Third Edition by : John C. Brocklebank, Ph.D.
Download or read book SAS for Forecasting Time Series, Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.
Book Synopsis Applied Data Mining by : Paolo Giudici
Download or read book Applied Data Mining written by Paolo Giudici and published by John Wiley & Sons. This book was released on 2005-09-27 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining can be defined as the process of selection, explorationand modelling of large databases, in order to discover models andpatterns. The increasing availability of data in the currentinformation society has led to the need for valid tools for itsmodelling and analysis. Data mining and applied statistical methodsare the appropriate tools to extract such knowledge from data.Applications occur in many different fields, including statistics,computer science, machine learning, economics, marketing andfinance. This book is the first to describe applied data mining methodsin a consistent statistical framework, and then show how they canbe applied in practice. All the methods described are eithercomputational, or of a statistical modelling nature. Complexprobabilistic models and mathematical tools are not used, so thebook is accessible to a wide audience of students and industryprofessionals. The second half of the book consists of nine casestudies, taken from the author's own work in industry, thatdemonstrate how the methods described can be applied to realproblems. Provides a solid introduction to applied data mining methods ina consistent statistical framework Includes coverage of classical, multivariate and Bayesianstatistical methodology Includes many recent developments such as web mining,sequential Bayesian analysis and memory based reasoning Each statistical method described is illustrated with real lifeapplications Features a number of detailed case studies based on appliedprojects within industry Incorporates discussion on software used in data mining, withparticular emphasis on SAS Supported by a website featuring data sets, software andadditional material Includes an extensive bibliography and pointers to furtherreading within the text Author has many years experience teaching introductory andmultivariate statistics and data mining, and working on appliedprojects within industry A valuable resource for advanced undergraduate and graduatestudents of applied statistics, data mining, computer science andeconomics, as well as for professionals working in industry onprojects involving large volumes of data - such as in marketing orfinancial risk management.
Book Synopsis Statistical Data Mining Using SAS Applications by : George Fernandez
Download or read book Statistical Data Mining Using SAS Applications written by George Fernandez and published by CRC Press. This book was released on 2010-06-18 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Data Mining Using SAS Applications, Second Edition describes statistical data mining concepts and demonstrates the features of user-friendly data mining SAS tools. Integrating the statistical and graphical analysis tools available in SAS systems, the book provides complete statistical data mining solutions without writing SAS program co
Book Synopsis Handbook of Statistical Analysis and Data Mining Applications by : Robert Nisbet
Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Robert Nisbet and published by Elsevier. This book was released on 2017-11-09 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Data Mining Using SAS Enterprise Miner by : Randall Matignon
Download or read book Data Mining Using SAS Enterprise Miner written by Randall Matignon and published by John Wiley & Sons. This book was released on 2007-08-03 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is a part of the Enterprise Miner software with regard to SEMMA design and data mining analysis. Data Mining Using SAS Enterprise Miner introduces readers to a wide variety of data mining techniques and explains the purpose of-and reasoning behind-every node that is a part of the Enterprise Miner software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes in SAS Enterprise Miner v4.3, followed by detailed explanations of configuration settings that are located within each node. Features of the book include: The exploration of node relationships and patterns using data from an assortment of computations, charts, and graphs commonly used in SAS procedures A step-by-step approach to each node discussion, along with an assortment of illustrations that acquaint the reader with the SAS Enterprise Miner working environment Descriptive detail of the powerful Score node and associated SAS code, which showcases the important of managing, editing, executing, and creating custom-designed Score code for the benefit of fair and comprehensive business decision-making Complete coverage of the wide variety of statistical techniques that can be performed using the SEMMA nodes An accompanying Web site that provides downloadable Score code, training code, and data sets for further implementation, manipulation, and interpretation as well as SAS/IML software programming code This book is a well-crafted study guide on the various methods employed to randomly sample, partition, graph, transform, filter, impute, replace, cluster, and process data as well as interactively group and iteratively process data while performing a wide variety of modeling techniques within the process flow of the SAS Enterprise Miner software. Data Mining Using SAS Enterprise Miner is suitable as a supplemental text for advanced undergraduate and graduate students of statistics and computer science and is also an invaluable, all-encompassing guide to data mining for novice statisticians and experts alike.
Book Synopsis Exploring SAS Viya by : Sas Education
Download or read book Exploring SAS Viya written by Sas Education and published by . This book was released on 2020-01-10 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS Visual Data Mining and Machine Learning, powered by SAS Viya, means that users of all skill levels can visually explore data on their own while drawing on powerful in-memory technologies for faster analytic computations and discoveries. You can manually program with custom code or use the features in SAS Studio, Model Studio, and SAS Visual Analytics to automate your data manipulation and modeling. These programs offer a flexible, easy-to-use, self-service environment that can scale on an enterprise-wide level. In this book, we will explore some of the many features of SAS Visual Data Mining and Machine Learning including: programming in the Python interface; new, advanced data mining and machine learning procedures; pipeline building in Model Studio, and model building and comparison in SAS Visual Analytics.
Book Synopsis Predictive Modeling with SAS Enterprise Miner by : Kattamuri S. Sarma
Download or read book Predictive Modeling with SAS Enterprise Miner written by Kattamuri S. Sarma and published by SAS Institute. This book was released on 2017-07-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: « Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--
Book Synopsis Business Forecasting by : Michael Gilliland
Download or read book Business Forecasting written by Michael Gilliland and published by John Wiley & Sons. This book was released on 2015-12-17 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive collection of the field's most provocative, influential new work Business Forecasting compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative ideas from forecasting researchers and practitioners, on topics including accuracy metrics, benchmarking, modeling of problem data, and overcoming dysfunctional behaviors. Its coverage includes often-overlooked issues at the forefront of research, such as uncertainty, randomness, and forecastability, as well as emerging areas like data mining for forecasting. The articles present critical analysis of current practices and consideration of new ideas. With a mix of formal, rigorous pieces and brief introductory chapters, the book provides practitioners with a comprehensive examination of the current state of the business forecasting field. Forecasting performance is ultimately limited by the 'forecastability' of the data. Yet failing to recognize this, many organizations continue to squander resources pursuing unachievable levels of accuracy. This book provides a wealth of ideas for improving all aspects of the process, including the avoidance of wasted efforts that fail to improve (or even harm) forecast accuracy. Analyzes the most prominent issues in business forecasting Investigates emerging approaches and new methods of analysis Combines forecasts to improve accuracy Utilizes Forecast Value Added to identify process inefficiency The business environment is evolving, and forecasting methods must evolve alongside it. This compilation delivers an array of new tools and research that can enable more efficient processes and more accurate results. Business Forecasting provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes.
Book Synopsis Genetic Programming Theory and Practice XI by : Rick Riolo
Download or read book Genetic Programming Theory and Practice XI written by Rick Riolo and published by Springer Science & Business Media. This book was released on 2014-04-01 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of injecting expert knowledge in evolutionary search, analysis of problem difficulty and required GP algorithm complexity, foundations in running GP on the cloud – communication, cooperation, flexible implementation, and ensemble methods. Additional focal points for GP symbolic regression are: (1) The need to guarantee convergence to solutions in the function discovery mode; (2) Issues on model validation; (3) The need for model analysis workflows for insight generation based on generated GP solutions – model exploration, visualization, variable selection, dimensionality analysis; (4) Issues in combining different types of data. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Book Synopsis Practical Business Analytics Using SAS by : Shailendra Kadre
Download or read book Practical Business Analytics Using SAS written by Shailendra Kadre and published by Apress. This book was released on 2015-02-07 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios. The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations. The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life. Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes: More than 200 examples and exercises, including code and datasets for practice. Relevant examples for all industries. Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course. Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before.
Book Synopsis Data Preparation for Data Mining Using SAS by : Mamdouh Refaat
Download or read book Data Preparation for Data Mining Using SAS written by Mamdouh Refaat and published by Elsevier. This book was released on 2010-07-27 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining views find little “how to information? And are you, like most analysts, preparing the data in SAS? This book is intended to fill this gap as your source of practical recipes. It introduces a framework for the process of data preparation for data mining, and presents the detailed implementation of each step in SAS. In addition, business applications of data mining modeling require you to deal with a large number of variables, typically hundreds if not thousands. Therefore, the book devotes several chapters to the methods of data transformation and variable selection. A complete framework for the data preparation process, including implementation details for each step. The complete SAS implementation code, which is readily usable by professional analysts and data miners. A unique and comprehensive approach for the treatment of missing values, optimal binning, and cardinality reduction. Assumes minimal proficiency in SAS and includes a quick-start chapter on writing SAS macros.
Book Synopsis Applied Econometrics Using the SAS System by : Vivek Ajmani
Download or read book Applied Econometrics Using the SAS System written by Vivek Ajmani and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first cutting-edge guide to using the SAS® system for the analysis of econometric data Applied Econometrics Using the SAS® System is the first book of its kind to treat the analysis of basic econometric data using SAS®, one of the most commonly used software tools among today's statisticians in business and industry. This book thoroughly examines econometric methods and discusses how data collected in economic studies can easily be analyzed using the SAS® system. In addition to addressing the computational aspects of econometric data analysis, the author provides a statistical foundation by introducing the underlying theory behind each method before delving into the related SAS® routines. The book begins with a basic introduction to econometrics and the relationship between classical regression analysis models and econometric models. Subsequent chapters balance essential concepts with SAS® tools and cover key topics such as: Regression analysis using Proc IML and Proc Reg Hypothesis testing Instrumental variables analysis, with a discussion of measurement errors, the assumptions incorporated into the analysis, and specification tests Heteroscedasticity, including GLS and FGLS estimation, group-wise heteroscedasticity, and GARCH models Panel data analysis Discrete choice models, along with coverage of binary choice models and Poisson regression Duration analysis models Assuming only a working knowledge of SAS®, this book is a one-stop reference for using the software to analyze econometric data. Additional features include complete SAS® code, Proc IML routines plus a tutorial on Proc IML, and an appendix with additional programs and data sets. Applied Econometrics Using the SAS® System serves as a relevant and valuable reference for practitioners in the fields of business, economics, and finance. In addition, most students of econometrics are taught using GAUSS and STATA, yet SAS® is the standard in the working world; therefore, this book is an ideal supplement for upper-undergraduate and graduate courses in statistics, economics, and other social sciences since it prepares readers for real-world careers.
Book Synopsis Data Mining for Business Analytics by : Galit Shmueli
Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2017-09-12 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions www.dataminingbook.com Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.
Book Synopsis Business Forecasting by : Michael Gilliland
Download or read book Business Forecasting written by Michael Gilliland and published by John Wiley & Sons. This book was released on 2021-05-11 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.
Book Synopsis Data Mining Using SAS Applications by : George Fernandez
Download or read book Data Mining Using SAS Applications written by George Fernandez and published by CRC Press. This book was released on 2010-12-12 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods stress the use of visualization to thoroughly study the structure of data and check the validity of statistical models fitted to data. Learn how to convert PC databases to SAS data Discover sampling techniques to create training and validation samples Understand frequency data analysis for categorical data Explore supervised and unsupervised learning Master exploratory graphical techniques Acquire model validation techniques in regression and classification The text furnishes 13 easy-to-use SAS data mining macros designed to work with the standard SAS modules. No additional modules or previous experience in SAS programming is required. The author shows how to perform complete predictive modeling, including data exploration, model fitting, assumption checks, validation, and scoring new data, on SAS datasets in less than ten minutes!
Book Synopsis Applied Analytics through Case Studies Using SAS and R by : Deepti Gupta
Download or read book Applied Analytics through Case Studies Using SAS and R written by Deepti Gupta and published by Apress. This book was released on 2018-08-03 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills. What You'll Learn Understand analytics and basic data concepts Use an analytical approach to solve Industrial business problems Build predictive model with machine learning techniques Create and apply analytical strategies Who This Book Is For Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.
