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Chapman and Hall/CRC Pattern Recognition Algorithms for Data Mining - CRC Books

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Description

Master complex data challenges with Pattern Recognition Algorithms for Data Mining. This volume provides a unified framework for various pattern recognition tasks, combining theoretical foundations with experimental results. It is designed for those working with large datasets that present difficulties such as overlapping, intractable, or nonlinear boundary classes. Readers will explore a wide range of methodologies, including classical approaches and hybrid paradigms. The content covers essential processes like data condensation, feature selection, case generation, clustering, classification, and rule generation and evaluation. By integrating soft granular computing within soft frameworks, this book offers advanced perspectives on knowledge discovery and scalability. Whether you are studying computer science or working in machine learning, this text provides the necessary algorithms to handle complex data mining environments. It serves as a comprehensive resource for understanding how to navigate modern data structures through both traditional and evolving computational theories.

Key Features

Unified framework for pattern recognition tasks that integrates both theoretical concepts and experimental results for practical application.

Comprehensive coverage of essential data mining processes including feature selection, data condensation, and case generation.

Advanced methodologies for clustering, classification, and rule generation and evaluation to improve knowledge discovery.

Specialized focus on handling large datasets with nonlinear boundary classes or overlapping data points.

Exploration of hybrid paradigms and classical approaches to solve complex data mining problems.

Detailed insights into granular computing within soft frameworks to manage complex data environments.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
27 May 2004
Listed Since
05 February 2007

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