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
Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780123747655 .
One of the most popular stemming algorithms, the Porter stemmer, used a series of heuristic replacement rules to transform word tokens into their stemmed form (Porter, 1980).1 These rules have been refined in later versions into what is ...
Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, The Handbook of Data Mining presents comprehensive coverage of data mining concepts and techniques.
The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems
This is the sixth version of this successful text, and the first using Python.
This book presents some of the most important modeling and prediction techniques, along with relevant applications.
This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
This not-for-profit private corporation currently accredits hospitals in Asia, Europe, the Middle East and South America, and is seeking to expand its business further (Donahue and van Ostenberg, 2000). The JCI extends the Joint ...
Mooney, R. J., and Roy, L. (2000). Content-Based Book Recommending Using Learning for Text Categorization. Proceedings of DL-00, 5th ACM Conference on Digital Libraries. San Antonio, TX, ACM Press, New York: 195-204.
This - one of a kind - book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life ...