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World Scientific Publishing Company Clustering and Classification - Advanced Data Analysis Methods

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Description

This moderately advanced text explores clustering and related data analysis methods at the forefront of computational research. The book covers hierarchical clustering techniques, variable selection and weighting strategies, and additive trees alongside network models that bridge classical approaches with modern computational methods. It examines neural network relevance to clustering problems, discusses computational complexity's critical role in cluster analysis, and presents latent class approaches with theoretical foundations. The work includes detailed coverage of hierarchical classes models with applications in psychology and psychopathology, combinatorial data analysis methods, and clusterwise aggregation of relations. Authored by World Scientific Publishing Company, this comprehensive resource combines rigorous theory with practical methodologies for researchers and practitioners working with complex datasets.

Key Features

Hierarchical clustering and advanced variable selection techniques are thoroughly examined with weighting methods for improved cluster definition.

Additive trees and network models are presented alongside neural network approaches to enhance clustering performance and interpretation.

Latent class clustering approaches provide theoretical frameworks applicable to psychology, psychopathology, and social science research.

Combinatorial data analysis and clusterwise aggregation of relations methods address complex data structures beyond standard clustering.

Computational complexity analysis throughout ensures readers understand scalability and efficiency trade-offs in cluster analysis algorithms.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 January 1996
Listed Since
19 January 2007

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No barcode data available

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