Data Mining And Statistics For Decision Making

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Data Mining and Statistics for Decision Making

Author : Stéphane Tufféry
Publisher : John Wiley & Sons
ISBN 13 : 0470979283
Total Pages : 748 pages
Book Rating : 4.4/5 (79 download)

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Book Synopsis Data Mining and Statistics for Decision Making by : Stéphane Tufféry

Download or read book Data Mining and Statistics for Decision Making written by Stéphane Tufféry and published by John Wiley & Sons. This book was released on 2011-03-23 with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Mining and Statistics for Decision Making

Author : Tufféry
Publisher :
ISBN 13 : 9781119583820
Total Pages : 800 pages
Book Rating : 4.5/5 (838 download)

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Book Synopsis Data Mining and Statistics for Decision Making by : Tufféry

Download or read book Data Mining and Statistics for Decision Making written by Tufféry and published by . This book was released on 2020-11-06 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Statistical Analysis and Data Mining Applications

Author : Robert Nisbet
Publisher : Elsevier
ISBN 13 : 0124166458
Total Pages : 822 pages
Book Rating : 4.1/5 (241 download)

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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

Customer and Business Analytics

Author : Daniel S. Putler
Publisher : CRC Press
ISBN 13 : 149875970X
Total Pages : 315 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Customer and Business Analytics by : Daniel S. Putler

Download or read book Customer and Business Analytics written by Daniel S. Putler and published by CRC Press. This book was released on 2015-09-15 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.

Business Intelligence

Author : Carlo Vercellis
Publisher : John Wiley & Sons
ISBN 13 : 1119965470
Total Pages : 314 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Business Intelligence by : Carlo Vercellis

Download or read book Business Intelligence written by Carlo Vercellis and published by John Wiley & Sons. This book was released on 2011-08-10 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

Data Driven Decision Making using Analytics

Author : Parul Gandhi
Publisher : CRC Press
ISBN 13 : 1000506436
Total Pages : 150 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Data Driven Decision Making using Analytics by : Parul Gandhi

Download or read book Data Driven Decision Making using Analytics written by Parul Gandhi and published by CRC Press. This book was released on 2021-12-21 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining. Features: Covers descriptive statistics with respect to predictive analytics and business analytics. Discusses different data analytics platforms for real-time applications. Explain SMART business models. Includes algorithms in data sciences alongwith automated methods and models. Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics. This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.

Data Science for Business and Decision Making

Author : Luiz Paulo Fávero
Publisher : Academic Press
ISBN 13 : 0128112174
Total Pages : 1240 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Data Science for Business and Decision Making by : Luiz Paulo Fávero

Download or read book Data Science for Business and Decision Making written by Luiz Paulo Fávero and published by Academic Press. This book was released on 2019-04-11 with total page 1240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs

Real-world Data Mining

Author : Dursun Delen
Publisher : Pearson Education
ISBN 13 : 0133551075
Total Pages : 289 pages
Book Rating : 4.1/5 (335 download)

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Book Synopsis Real-world Data Mining by : Dursun Delen

Download or read book Real-world Data Mining written by Dursun Delen and published by Pearson Education. This book was released on 2015 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: As business becomes increasingly complex and global, decision-makers must act more rapidly and accurately, based on the best available evidence. Modern data mining and analytics is indispensable for doing this. Real-World Data Mining demystifies current best practices, showing how to use data mining and analytics to uncover hidden patterns and correlations, and leverage these to improve all business decision-making. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, Delen provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: data mining processes, methods, and techniques; the role and management of data; tools and metrics; text and web mining; sentiment analysis; and integration with cutting-edge Big Data approaches. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials.

Getting Started with Business Analytics

Author : David Roi Hardoon
Publisher : CRC Press
ISBN 13 : 1439896542
Total Pages : 192 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Getting Started with Business Analytics by : David Roi Hardoon

Download or read book Getting Started with Business Analytics written by David Roi Hardoon and published by CRC Press. This book was released on 2013-03-26 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts

Making Sense of Data

Author : Glenn J. Myatt
Publisher : John Wiley & Sons
ISBN 13 : 0470101016
Total Pages : 294 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Making Sense of Data by : Glenn J. Myatt

Download or read book Making Sense of Data written by Glenn J. Myatt and published by John Wiley & Sons. This book was released on 2007-02-26 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical, step-by-step approach to making sense out of data Making Sense of Data educates readers on the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. The author provides clear explanations that guide the reader to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. With a comprehensive collection of methods from both data analysis and data mining disciplines, this book successfully describes the issues that need to be considered, the steps that need to be taken, and appropriately treats technical topics to accomplish effective decision making from data. Readers are given a solid foundation in the procedures associated with complex data analysis or data mining projects and are provided with concrete discussions of the most universal tasks and technical solutions related to the analysis of data, including: * Problem definitions * Data preparation * Data visualization * Data mining * Statistics * Grouping methods * Predictive modeling * Deployment issues and applications Throughout the book, the author examines why these multiple approaches are needed and how these methods will solve different problems. Processes, along with methods, are carefully and meticulously outlined for use in any data analysis or data mining project. From summarizing and interpreting data, to identifying non-trivial facts, patterns, and relationships in the data, to making predictions from the data, Making Sense of Data addresses the many issues that need to be considered as well as the steps that need to be taken to master data analysis and mining.

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

Author : Gary Miner
Publisher : Academic Press
ISBN 13 : 012386979X
Total Pages : 1096 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications by : Gary Miner

Download or read book Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications written by Gary Miner and published by Academic Press. This book was released on 2012-01-11 with total page 1096 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications 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"--

Data Mining

Author : Robert Stahlbock
Publisher : Springer Science & Business Media
ISBN 13 : 1441912800
Total Pages : 387 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Data Mining by : Robert Stahlbock

Download or read book Data Mining written by Robert Stahlbock and published by Springer Science & Business Media. This book was released on 2009-11-10 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research. This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

Statistical Data Analytics

Author : Walter W. Piegorsch
Publisher : John Wiley & Sons
ISBN 13 : 111903065X
Total Pages : 227 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Statistical Data Analytics by : Walter W. Piegorsch

Download or read book Statistical Data Analytics written by Walter W. Piegorsch and published by John Wiley & Sons. This book was released on 2015-12-21 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.

Frontiers of Statistical Decision Making and Bayesian Analysis

Author : Ming-Hui Chen
Publisher : Springer Science & Business Media
ISBN 13 : 1441969446
Total Pages : 631 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Frontiers of Statistical Decision Making and Bayesian Analysis by : Ming-Hui Chen

Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen and published by Springer Science & Business Media. This book was released on 2010-07-24 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.

Descriptive Data Mining

Author : David L. Olson
Publisher : Springer
ISBN 13 : 9811371814
Total Pages : 130 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Descriptive Data Mining by : David L. Olson

Download or read book Descriptive Data Mining written by David L. Olson and published by Springer. This book was released on 2019-05-06 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of data mining methods demonstrated by software. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Diagnostic analytics can apply analysis to sensor input to direct control systems automatically. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on descriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic software support to data visualization. Chapter 3 covers fundamentals of market basket analysis, and Chapter 4 provides demonstration of RFM modeling, a basic marketing data mining tool. Chapter 5 demonstrates association rule mining. Chapter 6 is a more in-depth coverage of cluster analysis. Chapter 7 discusses link analysis. Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.

Making Sense of Data II

Author : Glenn J. Myatt
Publisher : John Wiley & Sons
ISBN 13 : 0470222808
Total Pages : 325 pages
Book Rating : 4.4/5 (72 download)

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Book Synopsis Making Sense of Data II by : Glenn J. Myatt

Download or read book Making Sense of Data II written by Glenn J. Myatt and published by John Wiley & Sons. This book was released on 2009-02-03 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.

Handbook of Methodological Approaches to Community-based Research

Author : Leonard Jason
Publisher : Oxford University Press
ISBN 13 : 0190243651
Total Pages : 409 pages
Book Rating : 4.1/5 (92 download)

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Book Synopsis Handbook of Methodological Approaches to Community-based Research by : Leonard Jason

Download or read book Handbook of Methodological Approaches to Community-based Research written by Leonard Jason and published by Oxford University Press. This book was released on 2016 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Handbook of Methodological Approaches to Community-Based Research is intended to aid the community-oriented researcher in learning about and applying cutting-edge quantitative, qualitative, and mixed methods approaches"--