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| sas text miner cost: Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition Randall S. Collica, 2017-03-23 Résumé : A working guide that uses real-world data, this step-by-step resource will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. -- |
| sas text miner cost: Text Mining and Analysis Dr. Goutam Chakraborty, Murali Pagolu, Satish Garla, 2014-11-22 Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program. |
| sas text miner cost: TEXT ANALYTICS WITH SAS , 2019 |
| sas text miner cost: Decision Trees for Business Intelligence and Data Mining Barry De Ville, 2006 This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications. |
| sas text miner cost: Handbook of Statistical Analysis and Data Mining Applications Robert Nisbet, John Elder, Gary D. Miner, 2009-05-14 The Handbook of Statistical Analysis and Data Mining Applications 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 one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book 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 industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. - Written By Practitioners for Practitioners - Non-technical explanations build understanding without jargon and equations - Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models - Practical advice from successful real-world implementations - Includes extensive case studies, examples, MS PowerPoint slides and datasets - CD-DVD with valuable fully-working 90-day software included: Complete Data Miner - QC-Miner - Text Miner bound with book |
| sas text miner cost: Practical Business Analytics Using SAS Shailendra Kadre, Venkat Reddy Konasani, 2015-02-07 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. |
| sas text miner cost: Data Mining Using SAS Enterprise Miner SAS Institute, 2003 |
| sas text miner cost: R and Data Mining Yanchang Zhao, 2012-12-31 R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. - Presents an introduction into using R for data mining applications, covering most popular data mining techniques - Provides code examples and data so that readers can easily learn the techniques - Features case studies in real-world applications to help readers apply the techniques in their work |
| sas text miner cost: Data Mining for the Masses Matthew North, 2012-08-18 Have you ever found yourself working with a spreadsheet full of data and wishing you could make more sense of the numbers? Have you reviewed sales or operations reports, wondering if there's a better way to anticipate your customers' needs? Perhaps you've even thought to yourself: There's got to be more to these figures than what I'm seeing! Data Mining can help, and you don't need a Ph.D. in Computer Science to do it. You can forecast staffing levels, predict demand for inventory, even sift through millions of lines of customer emails looking for common themes-all using data mining. It's easier than you might think. In Data Mining for the Masses, professor Matt North-a former risk analyst and database developer for eBay.com-uses simple examples, clear explanations and free, powerful, easy-to-use software to teach you the basics of data mining; techniques that can help you answer some of your toughest business questions. You've got data and you know it's got value, if only you can figure out how to unlock it. This book can show you how. Let's start digging! Through an agreement with the Global Text Project, an electronic version of this text is available online at (http://globaltext.terry.uga.edu/books). Proceeds from the sales of printed copies through Amazon enable the author to support the Global Text Project's goal of making electronic texts available to students in developing economies. |
| sas text miner cost: SAS Certified Specialist Prep Guide SAS Institute, 2019-02-11 The SAS® Certified Specialist Prep Guide: Base Programming Using SAS® 9.4 prepares you to take the new SAS 9.4 Base Programming -- Performance-Based Exam. This is the official guide by the SAS Global Certification Program. This prep guide is for both new and experienced SAS users, and it covers all the objectives that are tested on the exam. New in this edition is a workbook whose sample scenarios require you to write code to solve problems and answer questions. Answers for the chapter quizzes and solutions for the sample scenarios in the workbook are included. You will also find links to exam objectives, practice exams, and other resources such as the Base SAS® glossary and a list of practice data sets. Major topics include importing data, creating and modifying SAS data sets, and identifying and correcting both data syntax and programming logic errors. All exam topics are covered in these chapters: Setting Up Practice Data Basic Concepts Accessing Your Data Creating SAS Data Sets Identifying and Correcting SAS Language Errors Creating Reports Understanding DATA Step Processing BY-Group Processing Creating and Managing Variables Combining SAS Data Sets Processing Data with DO Loops SAS Formats and Informats SAS Date, Time, and Datetime Values Using Functions to Manipulate Data Producing Descriptive Statistics Creating Output Practice Programming Scenarios (Workbook) |
| sas text miner cost: Text Mining Techniques for Healthcare Provider Quality Determination: Methods for Rank Comparisons Cerrito, Patricia, 2009-08-31 The quest for quality in healthcare has led to attempts to develop models to determine which providers have the highest quality in healthcare, with the best outcomes for patients. Text Mining Techniques for Healthcare Provider Quality Determination: Methods for Rank Comparisons discusses the general practice of defining a patient severity index in order to make risk adjustments to compare patient outcomes across multiple providers with the intent of ranking the providers in terms of quality. This innovative reference source, valuable to medical practitioners, researchers, and academicians, brings together research from across the globe focusing on how severity indices are generally defined when determining the best outcome for patient |
| sas text miner cost: Artificial Cognition Systems Loula, Angelo, Gudwin, Ricardo, Queiroz, João, 2006-07-31 This book presents recent research efforts in Artificial Intelligence about building artificial systems capable of performing cognitive tasks. A fundamental issue addressed in this book is if these cognitive processes can have any meaningfulness to the artificial system being built--Provided by publisher. |
| sas text miner cost: OpenIntro Statistics David Diez, Christopher Barr, Mine Çetinkaya-Rundel, 2015-07-02 The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources. |
| sas text miner cost: Statistical and Machine-Learning Data Mining Bruce Ratner, 2012-02-28 The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has completely revised, reorganized, and repositioned the original chapters and produced 14 new chapters of creative and useful machine-learning data mining techniques. In sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. The statistical data mining methods effectively consider big data for identifying structures (variables) with the appropriate predictive power in order to yield reliable and robust large-scale statistical models and analyses. In contrast, the author's own GenIQ Model provides machine-learning solutions to common and virtually unapproachable statistical problems. GenIQ makes this possible — its utilitarian data mining features start where statistical data mining stops. This book contains essays offering detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. They address each methodology and assign its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with. |
| sas text miner cost: SAS Essentials Alan C. Elliott, Wayne A. Woodward, 2015-08-18 A step-by-step introduction to using SAS® statistical software as a foundational approach to data analysis and interpretation Presenting a straightforward introduction from the ground up, SAS® Essentials: Mastering SAS for Data Analytics, Second Edition illustrates SAS using hands-on learning techniques and numerous real-world examples. Keeping different experience levels in mind, the highly-qualified author team has developed the book over 20 years of teaching introductory SAS courses. Divided into two sections, the first part of the book provides an introduction to data manipulation, statistical techniques, and the SAS programming language. The second section is designed to introduce users to statistical analysis using SAS Procedures. Featuring self-contained chapters to enhance the learning process, the Second Edition also includes: Programming approaches for the most up-to-date version of the SAS platform including information on how to use the SAS University Edition Discussions to illustrate the concepts and highlight key fundamental computational skills that are utilized by business, government, and organizations alike New chapters on reporting results in tables and factor analysis Additional information on the DATA step for data management with an emphasis on importing data from other sources, combining data sets, and data cleaning Updated ANOVA and regression examples as well as other data analysis techniques A companion website with the discussed data sets, additional code, and related PowerPoint® slides SAS Essentials: Mastering SAS for Data Analytics, Second Edition is an ideal textbook for upper-undergraduate and graduate-level courses in statistics, data analytics, applied SAS programming, and statistical computer applications as well as an excellent supplement for statistical methodology courses. The book is an appropriate reference for researchers and academicians who require a basic introduction to SAS for statistical analysis and for preparation for the Basic SAS Certification Exam. |
| sas text miner cost: Abstracts of Conference Papers , 1984 |
| sas text miner cost: SAS and R Ken Kleinman, Nicholas J. Horton, 2014-07-17 An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent Tasks The first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and graphics, along with more complex applications. New to the Second Edition This edition now covers RStudio, a powerful and easy-to-use interface for R. It incorporates a number of additional topics, including using application program interfaces (APIs), accessing data through database management systems, using reproducible analysis tools, and statistical analysis with Markov chain Monte Carlo (MCMC) methods and finite mixture models. It also includes extended examples of simulations and many new examples. Enables Easy Mobility between the Two Systems Through the extensive indexing and cross-referencing, users can directly find and implement the material they need. SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Numerous example analyses demonstrate the code in action and facilitate further exploration. The datasets and code are available for download on the book’s website. |
| sas text miner cost: SAS Text Analytics for Business Applications Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis, 2019-03-29 Extract actionable insights from text and unstructured data. Information extraction is the task of automatically extracting structured information from unstructured or semi-structured text. SAS Text Analytics for Business Applications: Concept Rules for Information Extraction Models focuses on this key element of natural language processing (NLP) and provides real-world guidance on the effective application of text analytics. Using scenarios and data based on business cases across many different domains and industries, the book includes many helpful tips and best practices from SAS text analytics experts to ensure fast, valuable insight from your textual data. Written for a broad audience of beginning, intermediate, and advanced users of SAS text analytics products, including SAS Visual Text Analytics, SAS Contextual Analysis, and SAS Enterprise Content Categorization, this book provides a solid technical reference. You will learn the SAS information extraction toolkit, broaden your knowledge of rule-based methods, and answer new business questions. As your practical experience grows, this book will serve as a reference to deepen your expertise. |
| sas text miner cost: Applied Health Analytics and Informatics Using SAS Joseph M. Woodside, 2018-11 Leverage health data into insight! Applied Health Analytics and Informatics Using SAS describes health anamatics, a result of the intersection of data analytics and health informatics. Healthcare systems generate nearly a third of the world's data, and analytics can help to eliminate medical errors, reduce readmissions, provide evidence-based care, demonstrate quality outcomes, and add cost-efficient care. This comprehensive textbook includes data analytics and health informatics concepts, along with applied experiential learning exercises and case studies using SAS Enterprise MinerTM within the healthcare industry setting. Topics covered include: Sampling and modeling health data - both structured and unstructured Exploring health data quality Developing health administration and health data assessment procedures Identifying future health trends Analyzing high-performance health data mining models Applied Health Analytics and Informatics Using SAS is intended for professionals, lifelong learners, senior-level undergraduates, graduate-level students in professional development courses, health informatics courses, health analytics courses, and specialized industry track courses. This textbook is accessible to a wide variety of backgrounds and specialty areas, including administrators, clinicians, and executives. |
| sas text miner cost: Data Preparation for Data Mining Using SAS Mamdouh Refaat, 2010-07-27 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. |
| sas text miner cost: Capitalism and Desire Todd McGowan, 2016-09-20 Despite creating vast inequalities and propping up reactionary world regimes, capitalism has many passionate defenders—but not because of what it withholds from some and gives to others. Capitalism dominates, Todd McGowan argues, because it mimics the structure of our desire while hiding the trauma that the system inflicts upon it. People from all backgrounds enjoy what capitalism provides, but at the same time are told more and better is yet to come. Capitalism traps us through an incomplete satisfaction that compels us after the new, the better, and the more. Capitalism's parasitic relationship to our desires gives it the illusion of corresponding to our natural impulses, which is how capitalism's defenders characterize it. By understanding this psychic strategy, McGowan hopes to divest us of our addiction to capitalist enrichment and help us rediscover enjoyment as we actually experienced it. By locating it in the present, McGowan frees us from our attachment to a better future and the belief that capitalism is an essential outgrowth of human nature. From this perspective, our economic, social, and political worlds open up to real political change. Eloquent and enlivened by examples from film, television, consumer culture, and everyday life, Capitalism and Desire brings a new, psychoanalytically grounded approach to political and social theory. |
| sas text miner cost: Credit Risk Analytics Bart Baesens, Daniel Roesch, Harald Scheule, 2016-10-03 The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process. |
| sas text miner cost: Time Series Analysis Using SAS Enterprise Guide Timina Liu, Shuangzhe Liu, Lei Shi, 2020-02-19 This is the first book to present time series analysis using the SAS Enterprise Guide software. It includes some starting background and theory to various time series analysis techniques, and demonstrates the data analysis process and the final results via step-by-step extensive illustrations of the SAS Enterprise Guide software. This book is a practical guide to time series analyses in SAS Enterprise Guide, and is valuable resource that benefits a wide variety of sectors. |
| sas text miner cost: Fraud Analytics with SAS , 2019-06-21 SAS software provides many different techniques to monitor in real time and investigate your data, and several groundbreaking papers have been written to demonstrate how to use these techniques. Topics covered illustrate the power of SAS solutions that are available as tools for fraud analytics, highlighting a variety of domains, including money laundering, financial crime, and terrorism. Also available free as a PDF from: sas.com/books. |
| sas text miner cost: Research in Personnel and Human Resources Management M. Ronald Buckley, Anthony R. Wheeler, John E. Baur, Jonathon R. B. Halbesleben, 2020-07-24 Research in Personnel and Human Resources Management is designed to promote theory and research on important substantive and methodological topics in the field of human resources management. |
| sas text miner cost: Data Mining and Statistics for Decision Making Stéphane Tufféry, 2011-03-23 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. |
| sas text miner cost: Knowledge Mining Spiros Sirmakessis, 2006-06-10 Text mining is an exciting application ?eld and an area of scienti?c - search that is currently under rapid development. It uses techniques from well-established scienti?c ?elds (e. g. data mining, machine learning, infor- tion retrieval, natural language processing, case-based reasoning, statistics and knowledge management) in an e?ort to help people gain insight, und- stand and interpret large quantities of (usually) semi-structured and unstr- tured data. Despite the advances made during the last few years, many issues remain unresolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identi?ed, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the ?eld of Text Mining – especially in relation to IT – and whether there still remain areas to be covered. Knowledge Mining draws upon many of the key concepts of knowledge management, data mining and knowledge discovery, meta-analysis and data visualization. Within the context of scienti?c research, knowledge mining is principally concerned with the quantitative synthesis and visualization of - search results and ?ndings. The results of knowledge mining are increased scienti?c understanding along with improvements in research quality and value. Knowledge mining products can be used to highlight research opportunities, assist with the p- sentation of “best” scienti?c evidence, facilitate research portfolio mana- ment, as well as, facilitate policy setting and decision making. |
| sas text miner cost: Practical Text Analytics Murugan Anandarajan, Chelsey Hill, Thomas Nolan, 2018-10-19 This book introduces text analytics as a valuable method for deriving insights from text data. Unlike other text analytics publications, Practical Text Analytics: Maximizing the Value of Text Data makes technical concepts accessible to those without extensive experience in the field. Using text analytics, organizations can derive insights from content such as emails, documents, and social media. Practical Text Analytics is divided into five parts. The first part introduces text analytics, discusses the relationship with content analysis, and provides a general overview of text mining methodology. In the second part, the authors discuss the practice of text analytics, including data preparation and the overall planning process. The third part covers text analytics techniques such as cluster analysis, topic models, and machine learning. In the fourth part of the book, readers learn about techniques used to communicate insights from text analysis, including data storytelling. The final part of Practical Text Analytics offers examples of the application of software programs for text analytics, enabling readers to mine their own text data to uncover information. |
| sas text miner cost: Social Science Research Anol Bhattacherjee, 2012-03-16 This book is designed to introduce doctoral and graduate students to the process of scientific research in the social sciences, business, education, public health, and related disciplines. |
| sas text miner cost: Data Mining with Rattle and R Graham Williams, 2011-02-25 Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings. |
| sas text miner cost: Cost-Sensitive Machine Learning Balaji Krishnapuram, Shipeng Yu, R. Bharat Rao, 2011-12-19 In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and cleaningComputational cost for model fitting, validation, and testingCost of collecting features/attributes for test dataCost of user feedback collect |
| sas text miner cost: SAS 9.2 Language Reference SAS Publishing, 2009 Documents essential concepts for the DATA step, SAS features, and SAS files. |
| sas text miner cost: Software Applications: Concepts, Methodologies, Tools, and Applications Tiako, Pierre F., 2009-03-31 Includes articles in topic areas such as autonomic computing, operating system architectures, and open source software technologies and applications. |
| sas text miner cost: Organizational Learning and Knowledge: Concepts, Methodologies, Tools and Applications Management Association, Information Resources, 2011-07-31 Organizational Learning and Knowledge: Concepts, Methodologies, Tools and Applications demonstrates exhaustively the many applications, issues, and techniques applied to the science of recording, categorizing, using and learning from the experiences and expertise acquired by the modern organization. A much needed collection, this multi-volume reference presents the theoretical foundations, research results, practical case studies, and future trends to both inform the decisions facing today's organizations and the establish fruitful organizational practices for the future. Practitioners, researchers, and academics involved in leading organizations of all types will find useful, grounded resources for navigating the ever-changing organizational landscape. |
| sas text miner cost: Data Mining Cookbook Olivia Parr Rud, 2001-01 Increase profits and reduce costs by utilizing this collection of models of the most commonly asked data mining questions In order to find new ways to improve customer sales and support, and as well as manage risk, business managers must be able to mine company databases. This book provides a step-by-step guide to creating and implementing models of the most commonly asked data mining questions. Readers will learn how to prepare data to mine, and develop accurate data mining questions. The author, who has over ten years of data mining experience, also provides actual tested models of specific data mining questions for marketing, sales, customer service and retention, and risk management. A CD-ROM, sold separately, provides these models for reader use. |
| sas text miner cost: Unstructured Data Analytics Jean Paul Isson, 2018-03-02 Turn unstructured data into valuable business insight Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data. Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions. The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation. Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices. Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video. These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies. This book provides the baseline knowledge and the practical understanding companies need to put this data to work. Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence. You will learn: How to increase Customer Acquisition and Customer Retention with UDA The Power of UDA for Fraud Detection and Prevention The Power of UDA in Human Capital Management & Human Resource The Power of UDA in Health Care and Medical Research The Power of UDA in National Security The Power of UDA in Legal Services The Power of UDA for product development The Power of UDA in Sports The future of UDA From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source. Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage. Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis. |
| sas text miner cost: Cases on Health Outcomes and Clinical Data Mining: Studies and Frameworks Cerrito, Patricia, 2010-02-28 Because so much data is now becoming readily available to investigate health outcomes, it is important to examine just how statistical models are used to do this. This book studies health outcomes research using data mining techniques--Provided by publisher. |
| sas text miner cost: Enterprise Information Systems and Implementing IT Infrastructures: Challenges and Issues Parthasarathy, S., 2010-03-31 This book aims at identifying potential research problems and issues in the EIS such as Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM)--Provided by publisher. |
| sas text miner cost: Healthcare Operations Management, Fourth Edition Daniel B. McLaughlin, John R. Olson, PhD, Luv Sharma, PhD, 2022-01-26 Instructor resources: Test bank, PowerPoint slides, teaching notes for the chapter content and end of chapter exercises, Excel files and cases for selected chapters with accompanying teaching notes, and a transition guide to the new edition. Today's challenging healthcare landscape--with its complex web of reimbursement systems, workforce challenges, and governmental regulations--requires a platform for addressing issues and trends. Savvy healthcare managers know how to integrate and deploy strategies to produce significant operational improvements and increase effectiveness throughout an entire healthcare enterprise. Healthcare Operations Management explores the core principles of effective organizational operations and explains how they can be used to tackle healthcare-specific challenges, such as gaps in quality of care. Through an integrated approach, the authors provide a basic understanding of operations man-agement and share strategies for applying advanced process improvement programs, tools, and tech-niques in healthcare. This revised edition delves extensively into the role of technology in healthcare operations improve-ment, exploring the use and impact of digital approaches to care delivery and finance with an emphasis on big data and advanced analytics. Other new or updated topics include: •Waste reduction and cost management in the US healthcare system •Quality management factors contributing to improvement processes •Tools and techniques for successfully deploying Lean •Changes that extend the supply chain beyond the walls of the hospital or clinic Most chapters begin with a vignette showcasing a real-world example related to the chapter's concepts and conclude with discussion questions. Integrating content featured throughout the book, the final chapter outlines a model for continuous healthcare operations improvement that introduces an algo-rithm for choosing and applying the book's methods and strategies. The US healthcare system is filled with opportunities for significant operational improvements that can affect the delivery of patient care. With the tools and techniques presented in this book, current and fu-ture healthcare managers will be equipped to implement these enhancements—and achieve operational excellence. |
| sas text miner cost: Data Mining Your Website Jesus Mena, 1999-07-15 Turn Web data into knowledge about your customers. This exciting book will help companies create, capture, enhance, and analyze one of their most valuable new sources of marketing information-usage and transactional data from a website. A company's website is a primary point of contact with its customers and a medium in which visitor's actions are messages about who they are and what they want. Data Mining Your Website will teach you the tools, techniques, and technologies you'll need to profile current and potential customers and predict on-line interests and behavior. You'll learn how to extract from the huge pools of information your website generates, insights into on-line buying patterns, and how to apply this knowledge to design a website that better attracts, engages, and retains on-line customers. Data Mining Your Website explains how data mining is a foundation for the new field of web-based, interactive retailing, marketing, and advertising. This innovative book will help web developers and marketers, webmasters, and data management professionals harness powerful new tools and processes. The first book to apply data mining specifically to e-commerce Learn effective methods for gathering, managing, and mining Web customer information Use data mining to profile customers and create personalized e-commerce programs |
如何零基础自学SAS? - 知乎
SAS在四大统计软件中的地位，emmmmm我想想，据说世界500强超过350家在用sas，服不服？ 不管你服不服，反正我是服了 那么对于软件学习，我个人觉得还是系统的上课或者有一本教 …
选硬盘时，该选择SSD/SATA/SAS哪个好？ - 知乎
机械硬盘主要为sata和sas接口，目前家用类别的移动硬盘多为sata接口，sas接口则为企业级应用。 SAS可满足高性能、高可靠性的应用，SATA则满足大容量、非关键业务的应用。
为什么JMP统计软件在中国受众如此之少？ - 知乎
最近在一篇推文中得知sas旗下还有一款软件叫jmp，下载后感觉自己发现新大陆，制图非常方便美观，统计分析板块也基本齐全，但是在国内却鲜有人知，这是为什…
正态性检验的结果怎么看？ - 知乎
在SAS中Kolmogorov-Smirnov一般适用于样本量大于2000，Shapiro-Wilk用于2000以内的样本。 在SPSS中比较复杂，一般而言， 样本量<50 用夏皮洛-威尔克检验（Shapiro-Wilk, W检 …
如何查看自己的笔记本是哪种固态硬盘接口？ - 知乎
机械硬盘5种接口：ide、sata、scsi、sas、fc，比较常见的还是sata！ 固态硬盘的接口有sata、sata express、msata、pci-e、m.2、u.2，其中m.2是兼容pci-e和sata的。
为何3.5寸的机械硬盘需要额外的供电而2.5寸的就不需要？ - 知乎
我今天亲自试过之后的答案，12v1a的机顶盒电源足以带起大部分3.5寸硬盘，硬盘上的标注因该没什么问题，你们可以看看身边或者网图，一般启动电流不会超过标注的12v1a，也就是12w， …
Origin of the phrase, "There's more than one way to skin a cat."
Jun 29, 2011 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for …
word choice - Grandma and Nan, origins and differences? - English ...
Oct 4, 2012 · Etymology. The word nan for grandma is a shortening of the word nana.Both of these words probably are child pronunciations of the word nanny.
To trust someone as far as you can throw them
Apr 18, 2017 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for …
A Question About Quantifier Shift for "each of you" to "you each"
Dec 4, 2015 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for …
如何零基础自学SAS? - 知乎
SAS在四大统计软件中的地位，emmmmm我想想，据说世界500强超过350家在用sas，服不服？ 不管你服不服，反正我是服了 那么对于软件学习，我个人觉得还是系统的上课或者有一本教 …
选硬盘时，该选择SSD/SATA/SAS哪个好？ - 知乎
机械硬盘主要为sata和sas接口，目前家用类别的移动硬盘多为sata接口，sas接口则为企业级应用。 SAS可满足高性能、高可靠性的应用，SATA则满足大容量、非关键业务的应用。
为什么JMP统计软件在中国受众如此之少？ - 知乎
最近在一篇推文中得知sas旗下还有一款软件叫jmp，下载后感觉自己发现新大陆，制图非常方便美观，统计分析板块也基本齐全，但是在国内却鲜有人知，这是为什…
正态性检验的结果怎么看？ - 知乎
在SAS中Kolmogorov-Smirnov一般适用于样本量大于2000，Shapiro-Wilk用于2000以内的样本。 在SPSS中比较复杂，一般而言， 样本量<50 用夏皮洛-威尔克检验（Shapiro-Wilk, W检 …
如何查看自己的笔记本是哪种固态硬盘接口？ - 知乎
机械硬盘5种接口：ide、sata、scsi、sas、fc，比较常见的还是sata！ 固态硬盘的接口有sata、sata express、msata、pci-e、m.2、u.2，其中m.2是兼容pci-e和sata的。
为何3.5寸的机械硬盘需要额外的供电而2.5寸的就不需要？ - 知乎
我今天亲自试过之后的答案，12v1a的机顶盒电源足以带起大部分3.5寸硬盘，硬盘上的标注因该没什么问题，你们可以看看身边或者网图，一般启动电流不会超过标注的12v1a，也就是12w， …
Origin of the phrase, "There's more than one way to skin a cat."
Jun 29, 2011 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for …
word choice - Grandma and Nan, origins and differences?
Oct 4, 2012 · Etymology. The word nan for grandma is a shortening of the word nana.Both of these words probably are child pronunciations of the word nanny.
To trust someone as far as you can throw them
Apr 18, 2017 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for …
A Question About Quantifier Shift for "each of you" to "you each"
Dec 4, 2015 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for …
