Data Preparation for Data Mining, Volume 1

Front Cover
Morgan Kaufmann, 1999 - Computers - 540 pages
4 Reviews

Data Preparation for Data Mining addresses an issue unfortunately ignored by most authorities on data mining: data preparation. Thanks largely to its perceived difficulty, data preparation has traditionally taken a backseat to the more alluring question of how best to extract meaningful knowledge. But without adequate preparation of your data, the return on the resources invested in mining is certain to be disappointing.

Dorian Pyle corrects this imbalance. A twenty-five-year veteran of what has become the data mining industry, Pyle shares his own successful data preparation methodology, offering both a conceptual overview for managers and complete technical details for IT professionals. Apply his techniques and watch your mining efforts pay off-in the form of improved performance, reduced distortion, and more valuable results.

On the enclosed CD-ROM, you'll find a suite of programs as C source code and compiled into a command-line-driven toolkit. This code illustrates how the author's techniques can be applied to arrive at an automated preparation solution that works for you. Also included are demonstration versions of three commercial products that help with data preparation, along with sample data with which you can practice and experiment.

* Offers in-depth coverage of an essential but largely ignored subject.
* Goes far beyond theory, leading you-step by step-through the author's own data preparation techniques.
* Provides practical illustrations of the author's methodology using realistic sample data sets.
* Includes algorithms you can apply directly to your own project, along with instructions for understanding when automation is possible and when greater intervention is required.
* Explains how to identify and correct data problems that may be present in your application.
* Prepares miners, helping them head into preparation with a better understanding of data sets and their limitations.

  

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it's awesome..

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I guess that the vast field of data mining has various levels of knowledge. I bought this book with the hope that it would assist me in the data preparation of my dataset that I was going to mine for my MSc thesis.
In short, this book was the most trivial book on Data mining / preparation that I have ever read. Examples were on minute datasets that need hardly any preparation; endless pages on describing basic facts on data; and no clear real-life examples that match the level of data mining encountered in industry.
I am very disapointed and wish I did not buy this book.
 

Contents

Data Exploration as a Process
9
Supplemental Material
39
The Nature of the World
45
Supplemental Material
87
Chapter 4
125
Supplemental Material
189
Supplemental Material
271
Supplemental Material
286
ti Chapter 10
351
KB Supplemental Material
446
2
452
Using Prepared Data
483
Appendix
505
Index
513
About the Author
537
Copyright

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About the author (1999)

Dorian Pyle is Chief Scientist and Founder of PTI (www.pti.com), which develops and markets PowerhouseT predictive and explanatory analytics software. Dorian has over 20 years experience in artificial intelligence and machine learning techniques which are used in what is known today as "data mining" or "predictive analytics". He has applied this knowledge as a consultant with Knowledge Stream Partners, Xchange, Naviant, Thinking Machines, and Data Miners and with various companies directly involved in credit card marketing for banks and with manufacturing companies using industrial automation. In 1976 he was involved in building artificially intelligent machine learning systems utilizing the pioneering technologies that are currently known as neural computing and associative memories. He is current in and familiar with using the most advanced technologies in data mining including: entropic analysis (information theory), chaotic and fractal decomposition, neural technologies, evolution and genetic optimization, algebra evolvers, case-based reasoning, concept induction and other advanced statistical techniques.

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