Applied Data Mining: Statistical Methods for Business and Industry (Statistics in Practice) (Paperback)

by Paolo Giudici (Author) "Nowadays each individual and organization - business, family or institution - can access a large quantity of data and information about itself and its environment..." (more)
Key Phrases: Enterprise Miner, John Wiley, Cumulative Cumulative (more...)

Editorial Reviews

Review
"The extremely well written book by Paolo Giudici is important and useful, in this computer intensive age, to analyze and interpret massive date using data mining tools." (Journal of Statistical Computation and Simulation, February 2005)

"...enlightening to anyone entering the area of data mining...a nice balance between theory and applications...certainly recommend it..." (Short Book Reviews, 2004)

"...strength lies in the number and diversity of [these] case studies...extensive reference section...no hesitation in recommending this..." (Significance - new magazine of the Royal Statistical Society, Vol 1(2), 2004)

Product Description
Data mining can be defined as the process of selection, exploration and modelling of large databases, in order to discover models and patterns. The increasing availability of data in the current information society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract such knowledge from data. Applications occur in many different fields, including statistics, computer science, machine learning, economics, marketing and finance.

This book is the first to describe applied data mining methods in a consistent statistical framework, and then show how they can be applied in practice. All the methods described are either computational, or of a statistical modelling nature. Complex probabilistic models and mathematical tools are not used, so the book is accessible to a wide audience of students and industry professionals. The second half of the book consists of nine case studies, taken from the author's own work in industry, that demonstrate how the methods described can be applied to real problems.

• Provides a solid introduction to applied data mining methods in a consistent statistical framework
• Includes coverage of classical, multivariate and Bayesian statistical methodology
• Includes many recent developments such as web mining, sequential Bayesian analysis and memory based reasoning
• Each statistical method described is illustrated with real life applications
• Features a number of detailed case studies based on applied projects within industry
• Incorporates discussion on software used in data mining, with particular emphasis on SAS
• Supported by a website featuring data sets, software and additional material
• Includes an extensive bibliography and pointers to further reading within the text
• Author has many years experience teaching introductory and multivariate statistics and data mining, and working on applied projects within industry

A valuable resource for advanced undergraduate and graduate students of applied statistics, data mining, computer science and economics, as well as for professionals working in industry on projects involving large volumes of data - such as in marketing or financial risk management.

Data sets used in the case studies are available at ftp://ftp.wiley.co.uk/pub/books/giudici

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Product Details

• Paperback: 376 pages
• Publisher: Wiley; 1 edition (October 31, 2003)
• Language: English
• ISBN-10: 0470846798
• ISBN-13: 978-0470846797
• Product Dimensions: 9 x 6 x 0.9 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 3.6 out of 5 stars See all reviews (5 customer reviews)
• Amazon.com Sales Rank: #593,837 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

6 of 8 people found the following review helpful:

5.0 out of 5 stars An excellent case-study book, October 22, 2003

By	Anne (Toronto) - See all my reviews

I found the book very useful especially because it contains fully worked out case-studies which, supported by the theoretical chapters, give clear guidance on how to actually do data mining

3 of 4 people found the following review helpful:

5.0 out of 5 stars User-friendly textbook, July 5, 2006

By	Viviana Fernandez (Santiago, Chile) - See all my reviews (REAL NAME)

I recently purchased the book by Dr. Giudici and I found it very informative for someone who is becoming acquainted with data mining. I would classify the book as intermediate/advanced. For a future edition, a further discussion on the technical issues involving the estimation methods would be desirable, in my view.

I would definitely recommend this textbook for a Master's level course.

Viviana Fernandez
Department of Industrial Engineering
University of Chile

1.0 out of 5 stars Poor Prose, April 14, 2009

By	Hack (Oregon, USA) - See all my reviews

This book is a difficult read, not because of the subject matter, but because of the writing. The author may know what he is writing about, but has difficulty conveying that in English. There is knowledge in this book, but it takes a lot of effort to decode.