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| Author | : Alex Berson |
| Publisher | : McGraw-Hill Companies |
| Total Pages | : 548 |
| Release | : 2000 |
| Genre | : Computers |
| ISBN | : |
Learn how to use customer relationship management (CRM) techniques to give your company an edge in the competitive marketplace. --
| Author | : Ken Yale |
| Publisher | : Elsevier |
| Total Pages | : 824 |
| Release | : 2017-11-09 |
| Genre | : Mathematics |
| ISBN | : 0124166458 |
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
| Author | : Alex Berson |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2000 |
| Genre | : Data mining |
| ISBN | : |
| Author | : Robert Groth |
| Publisher | : Prentice Hall |
| Total Pages | : 312 |
| Release | : 2000 |
| Genre | : Artificial intelligence |
| ISBN | : |
PLEASE PROVIDE COURSE INFORMATION PLEASE PROVIDE
| Author | : Yanchang Zhao |
| Publisher | : Academic Press |
| Total Pages | : 493 |
| Release | : 2013-11-26 |
| Genre | : Computers |
| ISBN | : 0124115209 |
Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries Presents various case studies in real-world applications, which will help readers to apply the techniques in their work Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves
| Author | : Berson |
| Publisher | : Tata McGraw-Hill Education |
| Total Pages | : 0 |
| Release | : 2000 |
| Genre | : |
| ISBN | : 9780070402737 |
A unique comprehensive guide to the business and technology of developing effective Enterprise Customer Relationship management solutions using contemporary data mining techniques. With focus on implementation and data mining technology, this book gives readers the ability to recognize and track patterns within their data, giving them a key competitive advantage over competition.
| Author | : Carlos A. Mota Soares |
| Publisher | : IOS Press |
| Total Pages | : 196 |
| Release | : 2010 |
| Genre | : Computers |
| ISBN | : 1607506327 |
Data mining is already incorporated into the business processes in sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications.
| Author | : Hao Jiang |
| Publisher | : Springer |
| Total Pages | : 227 |
| Release | : 2019-05-10 |
| Genre | : Technology & Engineering |
| ISBN | : 3030165035 |
This book focuses on mobile data and its applications in the wireless networks of the future. Several topics form the basis of discussion, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data mining is addressed in the context of three applications: wireless communication optimization, applications of mobile data mining on the cellular networks of the future, and how mobile data shapes future cities. In the discussion of wireless communication optimization, both licensed and unlicensed spectra are exploited. Advanced topics include mobile offloading, resource sharing, user association, network selection and network coexistence. Mathematical tools, such as traditional convexappl/non-convex, stochastic processing and game theory are used to find objective solutions. Discussion of the applications of mobile data mining to cellular networks of the future includes topics such as green communication networks, 5G networks, and studies of the problems of cell zooming, power control, sleep/wake, and energy saving. The discussion of mobile data mining in the context of smart cities of the future covers applications in urban planning and environmental monitoring: the technologies of deep learning, neural networks, complex networks, and network embedded data mining. Mobile Data Mining and Applications will be of interest to wireless operators, companies, governments as well as interested end users.
| Author | : Michael J. A. Berry |
| Publisher | : John Wiley & Sons |
| Total Pages | : 671 |
| Release | : 2004-04-14 |
| Genre | : Computers |
| ISBN | : 0764569074 |
Packed with more than forty percent new and updated material,this edition shows business managers, marketing analysts, and datamining specialists how to harness fundamental data mining methodsand techniques to solve common types of business problems Each chapter covers a new data mining technique, and then showsreaders how to apply the technique for improved marketing, sales,and customer support The authors build on their reputation for concise, clear, andpractical explanations of complex concepts, making this book theperfect introduction to data mining More advanced chapters cover such topics as how to prepare datafor analysis and how to create the necessary infrastructure fordata mining Covers core data mining techniques, including decision trees,neural networks, collaborative filtering, association rules, linkanalysis, clustering, and survival analysis
| Author | : Ian H. Witten |
| Publisher | : Elsevier |
| Total Pages | : 665 |
| Release | : 2011-02-03 |
| Genre | : Computers |
| ISBN | : 0080890369 |
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
