by Dorian Pyle, Morgan Kaufmann, , PDF, pages, 5 MB. From: Date: A download of this excellent book is was available on the web. Data Preparation. Data Preparation for Data Mining by Dorian Pyle, , available at Book Depository with free delivery worldwide. Oxford and Oxford English are trade marks of Oxford University Press. ISBN 0 19 7 (with answers). ISBN 0 19
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Data Preparation for Data Mining addresses an issue unfortunately ignored by most ddata on data mining: 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 odrian 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.
Dorian Pyle. Data Preparation for Data Mining. Morgan – Temida
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.
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In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading. Back Discovering Knowledge in Data: Features 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.
Data preparation for data mining
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 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: Would you like to tell us about a lower preparatiom If you are a seller pre;aration this product, would you like to suggest updates through seller support?
Dorian Pyle. Data Preparation for Data Mining. Morgan – Temida – PDF Drive
Read more Read less. Discover Prime Book Box for Kids. Customers who viewed this item also viewed. Page 1 of 1 Start over Page 1 of 1. Discovering Knowledge in Data: An Introduction to Preparatuon Mining. Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists.
Customers who bought this item also bought. R for Data Science: Practical Machine Learning with H2O. From the Back Cover Data Preparation for Data Mining addresses an issue unfortunately ignored by most authorities on data mining: Morgan Kaufmann; 1 edition April 5, Language: I’d like to read this book on Kindle Don’t have a Kindle?
Share your thoughts with other customers. Write a customer review. Read reviews that mention data mining data preparation dorian pyle excellent book problems with data techniques subject important begin models process examples focus knowledge learn provides types. Showing of 15 reviews. Top Reviews Most recent Top Reviews. There was a problem filtering reviews right now. Please try again later. Dorian Pyle has written this book for practicing data analysts who need a toolbox of techniques to get data ready for exploration and modeling.
It is intended to fill ” The book’s twelve chapters can be organized into three groups. The first three daa data exploration as the larger context in which data mining is conducted.
The author reminds us that finding interesting and useful problems that data analysis can solve is at least as important as knowing how to solve them.
Chapters four through eight present common data problems and offer solutions. Processes include assembling data from archives and other sources, selectively removing variables, replacing missing observations, and normalizing distributions. The final four chapters are more specialized.
Chapter 9 discusses data problems that appear in time series data and other types of series data. Chapter 10 describes issues that may remain in data sets after problems with individual variables have been corrected. Chapter 11 describes why and how to conduct a “data survey” to learn the high-level features of a data set and prepare for more detailed analysis. The last chapter closes the book with modeling and analysis techniques–where most data mining books begin.
This doria is an excellent resource for practicing data miners. It’s coverage of data preparation is thorough; it connects well to other aspects of data mining; and it emphasizes overall purpose of making decisions with data. It provides an adequate statistical foundation and has a practical focus throughout. It is full of tips, tactics and techniques.
I have been helping folks learn Clementine – a data mining package – for several years. I have read a number of related books, but never got to this one until recently.
That was a mistake. For Prepatation, Sales, and Customer Relationship Managementthis should be the second book that they read. Statistics training can be of enormous benefit to data miners, but leads to certain predictable errors.
Not only that, many data miners already have statistics training and that just compounds the likelihood that they will make these mistakes when dlrian book author fails to show the difference clearly. Pyle performs consistently well in this regard.
He consistently focuses on the kinds of problems data miners are likely to see in their work.
Data Preparation for Data Mining – Dorian Pyle – Google Books
To give just a couple of examples: Few variables will be already stored as continuous, normally distributed variables; principle components analysis might sometimes be a problematic way to eliminate predictors and even be dangerous; missing versus “empty” data; constantly present non-linearity.
His practice data set has a real variety of variable types, and dozens of predictors. Then, time permitting; start reading specific books on modeling or software.
For instance, another Larose book has good, detailed coverage of algorithms, and some information on Clementine. There are so many different aspects to data quality, it boggles the mind. Pyle addresses each one in detail, with clear examples and explanations. The book is well-written and more importantly, understandable.
The way data is prepared and aggregated determines the picture one gets from the data. It must be done correctly from the start, or all downstream processing and conclusions are suspect.
The CD that comes with the book is pretty much useless, but aside from that caveat, this is a great book. Buy it – you won’t be disappointed. One person found this helpful. I’ve had the pleasure of listening to Dorian speak at seminars and even sharing a few brief words with him in person.
When he mentioned to me last year that he was working on this book I had no idea how thorough and complete it would be. In fact, I remember wondering to myself how anyone could get their hands around this difficult, yet important aspect of data mining. Anyone in the trenches will immediately understand the value of this book. Those just getting started in data mining will probably have no idea how much simpler their job just became.
My only criticism of this book is that its title obscures that fact that there is a wealth of general data mining information contained within it – practical well beyond the data preparation phase. To understand why and how certain data preparation techniques work is to go a long way towards appreciating subtleties throughout the rest of the data mining process. See all 15 reviews. Pages with related products. See and discover other items: There’s a problem loading this menu right now.
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