Handbook of Statistical Analysis and Data Mining Applications

"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 using Statistica, SAS and SPSS software. The book offers practical advice from successful real-world implementations. It includes extensive case studies, examples, MS PowerPoint slides and datasets. A CD-DVD with valuable fully-working 90-day software is included. 'Complete Data Miner - QC-Miner - Text Miner' is bound with book.

ISBN 0123747651   Pages 864 ISBN13 9780123747655 (What's this?)   Volumes 1 Publisher Elsevier Science Publishing Co Inc   Weight (grammes) 1633 Imprint Academic Press Inc   Published in San Diego Format Hardback   Height (mm) 235 Publication date 10 Jul 2009   Width (mm) 191 Library of Congress 2009008997   Spine width (mm) 38 DEWEY 519.5   Academic level Professional / Scholarly DEWEY edition DC22

1		The Background for Data Mining Practice
2		Theoretical Considerations for Data Mining
3		The Data Mining Process
4		Data Understanding and Preparation
5		Feature Selection
6		Accessory Tools for Doing Data Mining
7		Basic Algorithms for Data Mining: A Brief Overview
8		Advanced Algorithms for Data Mining
9		Text Mining and Natural Language Processing
10		The Three Most Common Data Mining Software Tools
11		Classification
12		Numerical Prediction
13		Model Evaluation and Enhancement
14		Medical Informatics
15		Bioinformatics
16		Customer Response Modeling
17		Fraud Detection
A		How to Use Data Miner Recipe
B		Data Mining for Aviation Safety
C		Predicting Movie Box-Office Receipts
D		Detecting Unsatisfied Customers: A Case Study
E		Credit Scoring
F		Churn Analysis
G		Text Mining: Automobile Brand Review
H		Predictive Process Control: QC-Data Mining
I		Business Administration in a Medical Industry
		More...

Data mining practitioners, here is your bible, the complete "driver's manual" for data mining. From starting the engine to handling the curves, this book covers the gamut of data mining techniques - including predictive analytics and text mining - illustrating how to achieve maximal value across business, scientific, engineering and medical applications. What are the best practices through each phase of a data mining project? How can you avoid the most treacherous pitfalls? The answers are in here. Going beyond its responsibility as a reference book, this resource also provides detailed tutorials with step-by-step instructions to drive established data mining software tools across real world applications. This way, newcomers start their engines immediately and experience hands-on success. If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner. - Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World "Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners." -- Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts)

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