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Springer Foundations and Methods in Combinatorial and Statistical Data Analysis

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Description

This comprehensive guide from Springer explores fundamental methods in clustering and combinatorial data analysis, presenting original formulations and ideas within this active research field. The book combines extensive introductions with formal mathematical developments and real case studies to help readers understand the mutual relationships between clustering methods from logical, combinatorial, and statistical perspectives. Using relational mathematical representation, the work handles all types of data structures in a precise and unified framework, making it an essential resource for researchers and practitioners seeking deeper insights into data analysis techniques and their theoretical foundations.

Key Features

Springer publication offering advanced treatment of clustering and combinatorial data analysis methods with mathematical rigour.

Presents new formulations and ideas within combinatorial and statistical data analysis through formal mathematical developments.

Includes extensive introductions and real case studies demonstrating practical applications of clustering methods.

Covers logical, combinatorial, and statistical facets of data analysis using relational mathematical representation.

Handles diverse data structures in a unified framework suitable for advanced information and knowledge processing.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
14 April 2016
Listed Since
13 November 2015

Barcode

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