Solving data mining through pattern recognition / Ruby L. Kennedy ... [et al.].

Contributor(s):

Kennedy, Ruby L

Material type: Text

TextSeries: Data Warehousing Institute series from Prentice Hall PTRPublication details: Upper Saddle River, N.J. : Prentice-Hall PTR, c1998.Description: xxv, {various pagings) : ill. + 1 computer laser optical discISBN:

0130950831

Subject(s):

Review: "Besides explaining the most current theories, Solving Data Mining Problems through Pattern Recognition takes a practical approach to overall project development concerns. The rigorous multi-step method includes defining the pattern recognition problem; collection, preparation, and preprocessing of data; choosing the appropriate algorithm and tuning algorithm parameters; and training, testing, and troubleshooting."--BOOK JACKET. "Pattern classification, estimation, and modeling are addressed using the following algorithms: linear and logistic regression, unimodal Gaussian and Gaussian mixture, multilayered perceptron/backpropagation and radial basis function neural networks, K nearest neighbors and nearest cluster, and K means clustering."--BOOK JACKET. "While some aspects of pattern recognition involve advanced mathematical principles, most successful projects rely on a strong element of human experience and intuition. Solving Data Mining Problems through Pattern Recognition provides a strong theoretical grounding for beginners, yet it also contains detailed models and insights into real-world problem-solving that will inspire more experienced users, be they database designers, modelers, or project leaders."--BOOK JACKET.

Average rating: 0.0 (0 votes)

Holdings ( 2 )
Title notes ( 4 )

Holdings
Item type	Current library	Home library	Collection	Shelving location	Call number	Status	Date due	Barcode	Item holds
AV Circulation	FIRST CITY UNIVERSITY COLLEGE	FIRST CITY UNIVERSITY COLLEGE	AV Circulation	CD Cabinet1	006.3 KEN (Browse shelf(Opens below))	Available		DD480
Open Collection	FIRST CITY UNIVERSITY COLLEGE	FIRST CITY UNIVERSITY COLLEGE	Open Collection	FCUC Library	006.3 KEN (Browse shelf(Opens below))	Available		00010004

Total holds: 0

Accompanying CD-ROM held at Circulation Desk : DD480.

Includes bibliographical references and index.

"Besides explaining the most current theories, Solving Data Mining Problems through Pattern Recognition takes a practical approach to overall project development concerns. The rigorous multi-step method includes defining the pattern recognition problem; collection, preparation, and preprocessing of data; choosing the appropriate algorithm and tuning algorithm parameters; and training, testing, and troubleshooting."--BOOK JACKET. "Pattern classification, estimation, and modeling are addressed using the following algorithms: linear and logistic regression, unimodal Gaussian and Gaussian mixture, multilayered perceptron/backpropagation and radial basis function neural networks, K nearest neighbors and nearest cluster, and K means clustering."--BOOK JACKET. "While some aspects of pattern recognition involve advanced mathematical principles, most successful projects rely on a strong element of human experience and intuition. Solving Data Mining Problems through Pattern Recognition provides a strong theoretical grounding for beginners, yet it also contains detailed models and insights into real-world problem-solving that will inspire more experienced users, be they database designers, modelers, or project leaders."--BOOK JACKET.

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