Technical Mining Imperfect Data: Dealing with Contamination and Incomplete Records (repost) (0898715822)

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Mining Imperfect Data: Dealing with Contamination and Incomplete Records

Data mining is concerned with the analysis of databases large enough that various anomalies, including outliers, incomplete data records, and more subtle phenomena such as misalignment errors, are virtually certain to be present. Mining Imperfect Data: Dealing with Contamination and Incomplete Records describes in detail a number of these problems, as well as their sources, their consequences, their detection, and their treatment. Specific strategies for data pretreatment and analytical validation that are broadly applicable are described, making them useful in conjunction with most data mining analysis methods. Examples are presented to illustrate the performance of the pretreatment and validation methods in a variety of situations; these include simulation-based examples in which "correct" results are known unambiguously as well as real data examples that illustrate typical cases met in practice.

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	Programming Mining Imperfect Data: Dealing with Contamination and Incomplete Records Mining Imperfect Data: Dealing with Contamination and Incomplete Records305 pages \| SIAM: Society for Industrial and Applied Mathematics (April 1, 2005) \| ISBN: 0898715822 \| PDF \| 16 MbThis book thoroughly discusses the varying problems tha ...
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