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Springer Rough Sets and Data Mining - Analysis of Imprecise Data

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Description

Rough Sets and Data Mining: Analysis of Imprecise Data is an edited research collection examining the latest advances in rough set theory and its practical applications in data mining. This comprehensive work presents chapters by leading scholars in the field, addressing how to discover dependencies within datasets and reason effectively about vague, uncertain and imprecise information. The book balances rigorous theoretical foundations with practical guidance, including coverage of rough set tools designed for real-world database mining operations. Ideal for researchers and practitioners working with complex, ambiguous data, this Springer publication from Kluwer Academic Publishers provides both conceptual understanding and technical resources for implementing rough set methodologies in data analysis projects.

Key Features

Rough Sets and Data Mining covers recent developments in rough set theory with contributions from leading scholars in computing and data science.

The book includes fundamental research explanations alongside practical rough set tools for mining databases and discovering data dependencies.

Analysis of Imprecise Data addresses reasoning about vague, uncertain and imprecise information within datasets using rough set approaches.

Published by Kluwer Academic Publishers through Springer, this research collection offers academic rigour for database management and data storage applications.

The used book in good condition provides affordable access to advanced topics in rough sets and computational data analysis methodologies.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 November 1996
Listed Since
16 February 2007

Barcode

No barcode data available

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