Mining Imperfect Data
Dealing with Contamination and Incomplete Records
By (author) Ronald K. Pearson
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Mining Imperfect Data by Ronald K. Pearson
Book DescriptionThis book thoroughly discusses the varying problems that occur in data mining, including their sources, consequences, detection, and 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 illustrate the performance of the pretreatment and validation methods in a variety of situations. The book, which deals with a wider range of data anomalies than are usually treated, includes a discussion of detecting anomalies through generalized sensitivity analysis (GSA), a process of identifying inconsistencies using systematic and extensive comparisons of results obtained by analysis of exchangeable datasets or subsets. Real data is made extensive use of, both in the form of a detailed analysis of a few real datasets and various published examples. A succinct introduction to functional equations illustrates their utility in describing various forms of qualitative behavior for useful data characterizations.
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Book DetailsISBN: 9780898715828
(228mm x 152mm x 16mm)
Imprint: Society for Industrial & Applied Mathematics,U.S.
Publisher: Society for Industrial & Applied Mathematics,U.S.
Publish Date: 1-Apr-2005
Country of Publication: United States
Books By Author Ronald K. Pearson
Discrete-time Dynamic Models, Hardback (April 1999)» View all books by Ronald K. Pearson
Fuelled by advances in computer technology, model-based approaches to the control of industrial processes are now widespread. This text provides practical insight into model selection for chemical processes and emphasizes structures suitable for control system design.
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Author Biography - Ronald K. Pearson
Ronald K. Pearson is Senior Scientist with ProSanos Corporation and holds an adjunct faculty position at Jefferson Medical College. His primary research interests are in the areas of nonlinear discrete-time dynamical models, exploratory data analysis, and nonlinear digital signal processing. He is author of the book Discrete-Time Dynamic Models (Oxford University Press, 1999) and coauthor of the book Identification and Control Using Volterra Models (Springer, 2001). He has published three encyclopedia articles and approximately 100 journal and conference papers.
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