Handbook of Statistical Analysis and Data Mining Applications
Language: English
Published by Academic Press Nov 2017, 2017
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
Neuware - 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.…
Seller Inventory # 9780124166325
- Title
- Handbook of Statistical Analysis and Data Mining Applications
- Author
- Ken Yale
- Publisher
- Academic Press Nov 2017
- Publication year
- 2017
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0124166326
- ISBN 13
- 9780124166325
- Edition
- 2nd Edition
- Item weight
- 1,820 grams
- Dimensions
- 242x192x44 mm
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
"Synopsis" may belong to another edition of this title.
About the Author
His prior experience includes: medical director and vice president of clinical solutions at ActiveHealth Management/Aetna, chief executive of innovation incubator business unit at UnitedHealth Group Community & State, strategic counsel for Johnson & Johnson, corporate vice president of CorSolutions and Matria Healthcare, senior vice president and general counsel at EduNeering, and founder and CEO of Advanced Health Solutions. Dr. Yale previously worked in the federal government as Commissioned Officer in the US Public Health Service, Legislative Counsel in the US Senate, Special Assistant to the President and Executive Director of the White House Domestic Policy Council, and Chief of Staff of the White House Office of Science and Technology.
Dr. Yale provides leadership and actively participates with industry organizations, including the American Medical Informatics Association - Workgroup on Genomics and Translational Bioinformatics; Bloomberg/BNA Health Insurance Advisory Board; Healthcare Information and Management Systems Society; and the URAC Accreditation Organization. He is a frequent speaker and author on health and technology topics, including the books “Managed Care Compliance Guide, “Clinical Integration: Population Health and Accountable Care, tutorial author in “Practical Predictive Analytics and Decisioning Systems for Medicine, and editor with “Statistical Analysis and Data Mining Applications Second Edition.
Bob Nisbet, PhD, is a Data Scientist, currently modeling precancerous colon polyp presence with clinical data at the UC-Irvine Medical Center. He has experience in predictive modeling in Telecommunications, Insurance, Credit, Banking. His academic experience includes teaching in Ecology and in Data Science. His industrial experience includes predictive modeling at AT&T, NCR, and FICO. He has worked also in Insurance, Credit, membership organizations (e.g. AAA), Education, and Health Care industries. He retired as an Assistant Vice President of Santa Barbara Bank & Trust in charge of business intelligence reporting and customer relationship management (CRM) modeling.
Dr. Gary Miner PhD received a B.S. from Hamline University, St. Paul, MN, with biology, chemistry, and education majors; an M.S. in zoology and population genetics from the University of Wyoming; and a Ph.D. in biochemical genetics from the University of Kansas as the recipient of a NASA pre-doctoral fellowship. He pursued additional National Institutes of Health postdoctoral studies at the U of Minnesota and U of Iowa eventually becoming immersed in the study of affective disorders and Alzheimer's disease.
In 1985, he and his wife, Dr. Linda Winters-Miner, founded the Familial Alzheimer's Disease Research Foundation, which became a leading force in organizing both local and international scientific meetings, bringing together all the leaders in the field of genetics of Alzheimer's from several countries, resulting in the first major book on the genetics of Alzheimer’s disease. In the mid-1990s, Dr. Miner turned his data analysis interests to the business world, joining the team at StatSoft and deciding to specialize in data mining. He started developing what eventually became the Handbook of Statistical Analysis and Data Mining Applications (co-authored with Drs. Robert A. Nisbet and John Elder), which received the 2009 American Publishers Award for Professional and Scholarly Excellence (PROSE). Their follow-up collaboration, Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications, also received a PROSE award in February of 2013. Gary was also co-author of “Practical Predictive Analytics and Decisioning Systems for Medicine (Academic Press, 2015). Overall, Dr. Miner’s career has focused on medicine and health issues, and the use of data analytics (statistics and predictive analytics) in analyzing medical data to decipher fact from fiction.
Gary has also served as Merit Reviewer for PCORI (Patient Centered Outcomes Research Institute) that awards grants for predictive analytics research into the comparative effectiveness and heterogeneous treatment effects of medical interventions including drugs among different genetic groups of patients; additionally he teaches on-line classes in ‘Introduction to Predictive Analytics’, ‘Text Analytics’, ‘Risk Analytics’, and ‘Healthcare Predictive Analytics’ for the University of California-Irvine. Recently, until ‘official retirement’ 18 months ago, he spent most of his time in his primary role as Senior Analyst-Healthcare Applications Specialist for Dell | Information Management Group, Dell Software (through Dell’s acquisition of StatSoft (www.StatSoft.com) in April 2014). Currently Gary is working on two new short popular books on ‘Healthcare Solutions for the USA’ and ‘Patient-Doctor Genomics Stories’.
"About the title" may belong to another edition of this title.
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