At a moderately advanced level, this book seeks to cover the areas of clustering and related methods of data analysis where major advances are being made. Topics include: hierarchical clustering, variable selection and weighting, additive trees and other network models, relevance of neural network models to clustering, the role of computational complexity in cluster analysis, latent class approaches to cluster analysis, theory and method with applications of a hierarchical classes model in psychology and psychopathology, combinatorial data analysis, clusterwise aggregation of relations, review of the Japanese-language results on clustering, review of the Russian-language results on clustering and multidimensional scaling, practical advances, and significance tests.
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"... there is such a wealth of information ... that even a beginner could learn a lot from it." Chance, 1997
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3 of 27 people found the following review helpful:
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cluestring and clasification,
By Vivi Sandradewi (Indonesia) - See all my reviews
This review is from: Clustering And Classification (Paperback)
metode cluestring of data with a hierarchical cluestring
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- Classification, 2nd Edition (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) by A.D. Gordon on 6 pages
- Cluster Analysis by Brian S. Everitt on 5 pages
- Market Research and Modeling: Progress and Prospects: A Tribute to Paul E. Green (International Series in Quantitative Marketing) by Yoram Wind on page 89, page 93, and page 98
- Classification, Clustering, and Data Mining Applications: Proceedings of the Meeting of the International Federation of Classification Societies ... Data Analysis, and Knowledge Organization) by David Banks on page 41, and page 360
- Understanding Green Consumer Behaviour: A Qualitative Cognitive Approach (Routledge Studies in Consumer Research) by Sigmund A. Wagner in Back Matter (1), and Back Matter (2)
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