Classification and Multivariate Analysis for Complex Data Structures: Studies in Classification, Data Analysis, and Knowledge Organization
Editat de Bernard Fichet, Domenico Piccolo, Rosanna Verde, Maurizio Vichien Limba Engleză Paperback – 5 mar 2011
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Specificații
ISBN-13: 9783642133114
ISBN-10: 3642133118
Pagini: 496
Ilustrații: XIX, 473 p. 110 illus., 34 illus. in color.
Dimensiuni: 155 x 235 x 30 mm
Greutate: 0.6 kg
Ediția:2011
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Classification, Data Analysis, and Knowledge Organization
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642133118
Pagini: 496
Ilustrații: XIX, 473 p. 110 illus., 34 illus. in color.
Dimensiuni: 155 x 235 x 30 mm
Greutate: 0.6 kg
Ediția:2011
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Classification, Data Analysis, and Knowledge Organization
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Key Notes.- Classification and Discrimination.- Data Mining.- Robustness and Classification.- Categorical Data and Latent Class Approach.- Latent Variables and Related Methods.- Symbolic, Multivalued and Conceptual Data Analysis.- Spatial, Temporal, Streaming and Functional Data Analysis.- Bio and Health Science.
Textul de pe ultima copertă
The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.
Caracteristici
Latest advances in data analysis methods for multidimensional data With contributions by international experts Special attention to new methodological contributions from theoretical and applicative points of view Includes supplementary material: sn.pub/extras