Data Preparation for Data Mining
Porting UNIX Applications
Series: The Morgan Kaufmann Series in Data Management Systems;
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Product details:
- Edition number Repr.
- Publisher Elsevier Science
- Date of Publication 15 April 1999
- ISBN 9781558605299
- Binding Paperback
- No. of pages560 pages
- Size 235x191 mm
- Weight 1010 g
- Language English 0
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Long description:
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.
MoreTable of Contents:
PrefaceIntroductionChapter 1 Data Exploration As a ProcessChapter 2 The Nature of the World and Its Impact on Data PreparationChapter 3 Data Preparation as a ProcessChapter 4 Getting the Data: Basic PreparationChapter 5 Sampling, Variability and ConfidenceChapter 6 Handling Non-Numerical VariablesChapter 7 Normalizing and Redistributing VariablesChapter 8 Replacing Missing and Empty Values Chapter 9 Series VariablesChapter 10 Preparing the Data SetChapter 11 The Data SurveyChapter 12 Using Prepared DataAppendix A Using the Demonstration Code on the CDAppendix B Further ReadingIndex
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